Overview

Dataset statistics

Number of variables87
Number of observations20336
Missing cells444882
Missing cells (%)25.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.5 MiB
Average record size in memory696.0 B

Variable types

Numeric75
Unsupported2
Categorical10

Alerts

HR-min is highly correlated with HR-maxHigh correlation
HR-max is highly correlated with HR-minHigh correlation
SBP-min is highly correlated with MAP-minHigh correlation
SBP-max is highly correlated with MAP-maxHigh correlation
MAP-min is highly correlated with SBP-min and 1 other fieldsHigh correlation
MAP-max is highly correlated with SBP-max and 1 other fieldsHigh correlation
DBP-min is highly correlated with MAP-minHigh correlation
DBP-max is highly correlated with MAP-maxHigh correlation
BaseExcess-min is highly correlated with BaseExcess-max and 3 other fieldsHigh correlation
BaseExcess-max is highly correlated with BaseExcess-min and 3 other fieldsHigh correlation
HCO3-min is highly correlated with BaseExcess-min and 3 other fieldsHigh correlation
HCO3-max is highly correlated with BaseExcess-min and 2 other fieldsHigh correlation
pH-min is highly correlated with BaseExcess-min and 1 other fieldsHigh correlation
pH-max is highly correlated with BaseExcess-maxHigh correlation
PaCO2-min is highly correlated with HCO3-minHigh correlation
PaCO2-max is highly correlated with pH-minHigh correlation
AST-min is highly correlated with AST-maxHigh correlation
AST-max is highly correlated with AST-minHigh correlation
BUN-min is highly correlated with BUN-max and 2 other fieldsHigh correlation
BUN-max is highly correlated with BUN-min and 2 other fieldsHigh correlation
Alkalinephos-min is highly correlated with Alkalinephos-maxHigh correlation
Alkalinephos-max is highly correlated with Alkalinephos-minHigh correlation
Calcium-min is highly correlated with Calcium-maxHigh correlation
Calcium-max is highly correlated with Calcium-minHigh correlation
Chloride-min is highly correlated with Chloride-maxHigh correlation
Chloride-max is highly correlated with Chloride-minHigh correlation
Creatinine-min is highly correlated with BUN-min and 2 other fieldsHigh correlation
Creatinine-max is highly correlated with BUN-min and 2 other fieldsHigh correlation
Bilirubin_direct-min is highly correlated with Bilirubin_direct-max and 2 other fieldsHigh correlation
Bilirubin_direct-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Lactate-min is highly correlated with Lactate-maxHigh correlation
Lactate-max is highly correlated with Lactate-minHigh correlation
Phosphate-min is highly correlated with Phosphate-maxHigh correlation
Phosphate-max is highly correlated with Phosphate-minHigh correlation
Bilirubin_total-min is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Bilirubin_total-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
TroponinI-min is highly correlated with TroponinI-maxHigh correlation
TroponinI-max is highly correlated with TroponinI-minHigh correlation
Hct-min is highly correlated with Hct-max and 2 other fieldsHigh correlation
Hct-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-min is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
PTT-min is highly correlated with PTT-maxHigh correlation
PTT-max is highly correlated with PTT-minHigh correlation
WBC-min is highly correlated with WBC-maxHigh correlation
WBC-max is highly correlated with WBC-minHigh correlation
Fibrinogen-min is highly correlated with Fibrinogen-maxHigh correlation
Fibrinogen-max is highly correlated with Fibrinogen-minHigh correlation
Platelets-min is highly correlated with Platelets-maxHigh correlation
Platelets-max is highly correlated with Platelets-minHigh correlation
Age-min is highly correlated with Age-maxHigh correlation
Age-max is highly correlated with Age-minHigh correlation
Gender-min is highly correlated with Gender-maxHigh correlation
Gender-max is highly correlated with Gender-minHigh correlation
Unit1-min is highly correlated with Unit1-max and 2 other fieldsHigh correlation
Unit1-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-min is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
HospAdmTime-min is highly correlated with HospAdmTime-maxHigh correlation
HospAdmTime-max is highly correlated with HospAdmTime-minHigh correlation
ICULOS-max is highly correlated with Hours-min and 1 other fieldsHigh correlation
SepsisLabel-max is highly correlated with Sepsis-min and 1 other fieldsHigh correlation
Sepsis-min is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Sepsis-max is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Hours-min is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
Hours-max is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
HR-min is highly correlated with HR-maxHigh correlation
HR-max is highly correlated with HR-minHigh correlation
SBP-min is highly correlated with MAP-minHigh correlation
SBP-max is highly correlated with MAP-maxHigh correlation
MAP-min is highly correlated with SBP-min and 1 other fieldsHigh correlation
MAP-max is highly correlated with SBP-maxHigh correlation
DBP-min is highly correlated with MAP-minHigh correlation
BaseExcess-min is highly correlated with BaseExcess-max and 5 other fieldsHigh correlation
BaseExcess-max is highly correlated with BaseExcess-min and 3 other fieldsHigh correlation
HCO3-min is highly correlated with BaseExcess-min and 3 other fieldsHigh correlation
HCO3-max is highly correlated with BaseExcess-min and 4 other fieldsHigh correlation
pH-min is highly correlated with BaseExcess-minHigh correlation
pH-max is highly correlated with BaseExcess-maxHigh correlation
PaCO2-min is highly correlated with BaseExcess-min and 3 other fieldsHigh correlation
PaCO2-max is highly correlated with HCO3-max and 1 other fieldsHigh correlation
AST-min is highly correlated with AST-maxHigh correlation
AST-max is highly correlated with AST-minHigh correlation
BUN-min is highly correlated with BUN-max and 3 other fieldsHigh correlation
BUN-max is highly correlated with BUN-min and 3 other fieldsHigh correlation
Alkalinephos-min is highly correlated with Alkalinephos-maxHigh correlation
Alkalinephos-max is highly correlated with Alkalinephos-minHigh correlation
Calcium-min is highly correlated with Calcium-maxHigh correlation
Calcium-max is highly correlated with Calcium-minHigh correlation
Chloride-min is highly correlated with Chloride-maxHigh correlation
Chloride-max is highly correlated with Chloride-minHigh correlation
Creatinine-min is highly correlated with BUN-min and 4 other fieldsHigh correlation
Creatinine-max is highly correlated with BUN-min and 3 other fieldsHigh correlation
Bilirubin_direct-min is highly correlated with Bilirubin_direct-max and 2 other fieldsHigh correlation
Bilirubin_direct-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Lactate-min is highly correlated with Lactate-maxHigh correlation
Lactate-max is highly correlated with BaseExcess-min and 1 other fieldsHigh correlation
Phosphate-min is highly correlated with BUN-min and 2 other fieldsHigh correlation
Phosphate-max is highly correlated with BUN-max and 3 other fieldsHigh correlation
Bilirubin_total-min is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Bilirubin_total-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
TroponinI-min is highly correlated with TroponinI-maxHigh correlation
TroponinI-max is highly correlated with TroponinI-minHigh correlation
Hct-min is highly correlated with Hct-max and 2 other fieldsHigh correlation
Hct-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-min is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
PTT-min is highly correlated with PTT-maxHigh correlation
PTT-max is highly correlated with PTT-minHigh correlation
WBC-min is highly correlated with WBC-maxHigh correlation
WBC-max is highly correlated with WBC-minHigh correlation
Fibrinogen-min is highly correlated with Fibrinogen-maxHigh correlation
Fibrinogen-max is highly correlated with Fibrinogen-minHigh correlation
Platelets-min is highly correlated with Platelets-maxHigh correlation
Platelets-max is highly correlated with Platelets-minHigh correlation
Age-min is highly correlated with Age-maxHigh correlation
Age-max is highly correlated with Age-minHigh correlation
Gender-min is highly correlated with Gender-maxHigh correlation
Gender-max is highly correlated with Gender-minHigh correlation
Unit1-min is highly correlated with Unit1-max and 2 other fieldsHigh correlation
Unit1-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-min is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
HospAdmTime-min is highly correlated with HospAdmTime-maxHigh correlation
HospAdmTime-max is highly correlated with HospAdmTime-minHigh correlation
ICULOS-max is highly correlated with Hours-min and 1 other fieldsHigh correlation
SepsisLabel-max is highly correlated with Sepsis-min and 1 other fieldsHigh correlation
Sepsis-min is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Sepsis-max is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Hours-min is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
Hours-max is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
SBP-max is highly correlated with MAP-maxHigh correlation
MAP-max is highly correlated with SBP-max and 1 other fieldsHigh correlation
DBP-max is highly correlated with MAP-maxHigh correlation
BaseExcess-min is highly correlated with HCO3-min and 1 other fieldsHigh correlation
BaseExcess-max is highly correlated with HCO3-maxHigh correlation
HCO3-min is highly correlated with BaseExcess-min and 1 other fieldsHigh correlation
HCO3-max is highly correlated with BaseExcess-max and 1 other fieldsHigh correlation
pH-min is highly correlated with BaseExcess-minHigh correlation
AST-min is highly correlated with AST-maxHigh correlation
AST-max is highly correlated with AST-minHigh correlation
BUN-min is highly correlated with BUN-max and 2 other fieldsHigh correlation
BUN-max is highly correlated with BUN-min and 2 other fieldsHigh correlation
Alkalinephos-min is highly correlated with Alkalinephos-maxHigh correlation
Alkalinephos-max is highly correlated with Alkalinephos-minHigh correlation
Calcium-min is highly correlated with Calcium-maxHigh correlation
Calcium-max is highly correlated with Calcium-minHigh correlation
Chloride-min is highly correlated with Chloride-maxHigh correlation
Chloride-max is highly correlated with Chloride-minHigh correlation
Creatinine-min is highly correlated with BUN-min and 2 other fieldsHigh correlation
Creatinine-max is highly correlated with BUN-min and 2 other fieldsHigh correlation
Bilirubin_direct-min is highly correlated with Bilirubin_direct-max and 2 other fieldsHigh correlation
Bilirubin_direct-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Lactate-min is highly correlated with Lactate-maxHigh correlation
Lactate-max is highly correlated with Lactate-minHigh correlation
Phosphate-min is highly correlated with Phosphate-maxHigh correlation
Phosphate-max is highly correlated with Phosphate-minHigh correlation
Bilirubin_total-min is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
Bilirubin_total-max is highly correlated with Bilirubin_direct-min and 2 other fieldsHigh correlation
TroponinI-min is highly correlated with TroponinI-maxHigh correlation
TroponinI-max is highly correlated with TroponinI-minHigh correlation
Hct-min is highly correlated with Hct-max and 1 other fieldsHigh correlation
Hct-max is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-min is highly correlated with Hct-min and 2 other fieldsHigh correlation
Hgb-max is highly correlated with Hct-max and 1 other fieldsHigh correlation
PTT-min is highly correlated with PTT-maxHigh correlation
PTT-max is highly correlated with PTT-minHigh correlation
WBC-min is highly correlated with WBC-maxHigh correlation
WBC-max is highly correlated with WBC-minHigh correlation
Fibrinogen-min is highly correlated with Fibrinogen-maxHigh correlation
Fibrinogen-max is highly correlated with Fibrinogen-minHigh correlation
Platelets-min is highly correlated with Platelets-maxHigh correlation
Platelets-max is highly correlated with Platelets-minHigh correlation
Age-min is highly correlated with Age-maxHigh correlation
Age-max is highly correlated with Age-minHigh correlation
Gender-min is highly correlated with Gender-maxHigh correlation
Gender-max is highly correlated with Gender-minHigh correlation
Unit1-min is highly correlated with Unit1-max and 2 other fieldsHigh correlation
Unit1-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-min is highly correlated with Unit1-min and 2 other fieldsHigh correlation
Unit2-max is highly correlated with Unit1-min and 2 other fieldsHigh correlation
HospAdmTime-min is highly correlated with HospAdmTime-maxHigh correlation
HospAdmTime-max is highly correlated with HospAdmTime-minHigh correlation
ICULOS-max is highly correlated with Hours-min and 1 other fieldsHigh correlation
SepsisLabel-max is highly correlated with Sepsis-min and 1 other fieldsHigh correlation
Sepsis-min is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Sepsis-max is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Hours-min is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
Hours-max is highly correlated with ICULOS-max and 1 other fieldsHigh correlation
SepsisLabel-max is highly correlated with Sepsis-min and 1 other fieldsHigh correlation
Gender-min is highly correlated with Gender-maxHigh correlation
Unit2-max is highly correlated with Unit2-min and 2 other fieldsHigh correlation
Sepsis-min is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Gender-max is highly correlated with Gender-minHigh correlation
Unit2-min is highly correlated with Unit2-max and 2 other fieldsHigh correlation
Unit1-min is highly correlated with Unit2-max and 2 other fieldsHigh correlation
Unit1-max is highly correlated with Unit2-max and 2 other fieldsHigh correlation
Sepsis-max is highly correlated with SepsisLabel-max and 1 other fieldsHigh correlation
Temp-min has 235 (1.2%) missing values Missing
Temp-max has 235 (1.2%) missing values Missing
SBP-min has 258 (1.3%) missing values Missing
SBP-max has 258 (1.3%) missing values Missing
DBP-min has 7384 (36.3%) missing values Missing
DBP-max has 7384 (36.3%) missing values Missing
EtCO2-min has 20336 (100.0%) missing values Missing
EtCO2-max has 20336 (100.0%) missing values Missing
BaseExcess-min has 7684 (37.8%) missing values Missing
BaseExcess-max has 7684 (37.8%) missing values Missing
HCO3-min has 535 (2.6%) missing values Missing
HCO3-max has 535 (2.6%) missing values Missing
FiO2-min has 8349 (41.1%) missing values Missing
FiO2-max has 8349 (41.1%) missing values Missing
pH-min has 7155 (35.2%) missing values Missing
pH-max has 7155 (35.2%) missing values Missing
PaCO2-min has 7759 (38.2%) missing values Missing
PaCO2-max has 7759 (38.2%) missing values Missing
SaO2-min has 12373 (60.8%) missing values Missing
SaO2-max has 12373 (60.8%) missing values Missing
AST-min has 14443 (71.0%) missing values Missing
AST-max has 14443 (71.0%) missing values Missing
BUN-min has 427 (2.1%) missing values Missing
BUN-max has 427 (2.1%) missing values Missing
Alkalinephos-min has 14633 (72.0%) missing values Missing
Alkalinephos-max has 14633 (72.0%) missing values Missing
Calcium-min has 3789 (18.6%) missing values Missing
Calcium-max has 3789 (18.6%) missing values Missing
Chloride-min has 542 (2.7%) missing values Missing
Chloride-max has 542 (2.7%) missing values Missing
Creatinine-min has 461 (2.3%) missing values Missing
Creatinine-max has 461 (2.3%) missing values Missing
Bilirubin_direct-min has 19750 (97.1%) missing values Missing
Bilirubin_direct-max has 19750 (97.1%) missing values Missing
Glucose-min has 407 (2.0%) missing values Missing
Glucose-max has 407 (2.0%) missing values Missing
Lactate-min has 12603 (62.0%) missing values Missing
Lactate-max has 12603 (62.0%) missing values Missing
Magnesium-min has 1388 (6.8%) missing values Missing
Magnesium-max has 1388 (6.8%) missing values Missing
Phosphate-min has 3650 (17.9%) missing values Missing
Phosphate-max has 3650 (17.9%) missing values Missing
Potassium-min has 433 (2.1%) missing values Missing
Potassium-max has 433 (2.1%) missing values Missing
Bilirubin_total-min has 14566 (71.6%) missing values Missing
Bilirubin_total-max has 14566 (71.6%) missing values Missing
TroponinI-min has 19847 (97.6%) missing values Missing
TroponinI-max has 19847 (97.6%) missing values Missing
Hct-min has 364 (1.8%) missing values Missing
Hct-max has 364 (1.8%) missing values Missing
Hgb-min has 507 (2.5%) missing values Missing
Hgb-max has 507 (2.5%) missing values Missing
PTT-min has 4496 (22.1%) missing values Missing
PTT-max has 4496 (22.1%) missing values Missing
WBC-min has 625 (3.1%) missing values Missing
WBC-max has 625 (3.1%) missing values Missing
Fibrinogen-min has 17769 (87.4%) missing values Missing
Fibrinogen-max has 17769 (87.4%) missing values Missing
Platelets-min has 585 (2.9%) missing values Missing
Platelets-max has 585 (2.9%) missing values Missing
Unit1-min has 9522 (46.8%) missing values Missing
Unit1-max has 9522 (46.8%) missing values Missing
Unit2-min has 9522 (46.8%) missing values Missing
Unit2-max has 9522 (46.8%) missing values Missing
O2Sat-max is highly skewed (γ1 = -21.73522171) Skewed
ICULOS-min is highly skewed (γ1 = 59.42175818) Skewed
PatientID has unique values Unique
EtCO2-min is an unsupported type, check if it needs cleaning or further analysis Unsupported
EtCO2-max is an unsupported type, check if it needs cleaning or further analysis Unsupported
BaseExcess-min has 2278 (11.2%) zeros Zeros
BaseExcess-max has 3101 (15.2%) zeros Zeros

Reproduction

Analysis started2021-11-29 10:27:34.778469
Analysis finished2021-11-29 10:27:51.868463
Duration17.09 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

PatientID
Real number (ℝ≥0)

UNIQUE

Distinct20336
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10173.60651
Minimum1
Maximum20643
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:51.916777image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1017.75
Q15084.75
median10168.5
Q315252.25
95-th percentile19320.25
Maximum20643
Range20642
Interquartile range (IQR)10167.5

Descriptive statistics

Standard deviation5879.461518
Coefficient of variation (CV)0.5779132024
Kurtosis-1.192915145
Mean10173.60651
Median Absolute Deviation (MAD)5084
Skewness0.005160825078
Sum206890462
Variance34568067.75
MonotonicityStrictly increasing
2021-11-29T11:27:52.015102image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
< 0.1%
135561
 
< 0.1%
135631
 
< 0.1%
135621
 
< 0.1%
135611
 
< 0.1%
135601
 
< 0.1%
135591
 
< 0.1%
135581
 
< 0.1%
135571
 
< 0.1%
135551
 
< 0.1%
Other values (20326)20326
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
101
< 0.1%
ValueCountFrequency (%)
206431
< 0.1%
206421
< 0.1%
206411
< 0.1%
206401
< 0.1%
206391
< 0.1%
206381
< 0.1%
206371
< 0.1%
206361
< 0.1%
206351
< 0.1%
206341
< 0.1%

HR-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct193
Distinct (%)0.9%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean69.85490534
Minimum20
Maximum144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:52.116704image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile49
Q160
median69
Q378
95-th percentile93
Maximum144
Range124
Interquartile range (IQR)18

Descriptive statistics

Standard deviation13.47874653
Coefficient of variation (CV)0.1929534722
Kurtosis0.576808424
Mean69.85490534
Median Absolute Deviation (MAD)9
Skewness0.3800833214
Sum1420499.5
Variance181.6766081
MonotonicityNot monotonic
2021-11-29T11:27:52.222188image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60731
 
3.6%
70710
 
3.5%
68604
 
3.0%
67584
 
2.9%
65559
 
2.7%
63550
 
2.7%
72548
 
2.7%
75543
 
2.7%
66542
 
2.7%
64539
 
2.7%
Other values (183)14425
70.9%
ValueCountFrequency (%)
201
 
< 0.1%
211
 
< 0.1%
222
< 0.1%
231
 
< 0.1%
241
 
< 0.1%
253
< 0.1%
261
 
< 0.1%
273
< 0.1%
27.51
 
< 0.1%
283
< 0.1%
ValueCountFrequency (%)
1441
< 0.1%
1401
< 0.1%
1371
< 0.1%
1351
< 0.1%
134.51
< 0.1%
1332
< 0.1%
1301
< 0.1%
1291
< 0.1%
1272
< 0.1%
1262
< 0.1%

HR-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct256
Distinct (%)1.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean103.0772658
Minimum37
Maximum280
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:52.323217image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile75
Q190
median102
Q3115
95-th percentile136
Maximum280
Range243
Interquartile range (IQR)25

Descriptive statistics

Standard deviation18.90264183
Coefficient of variation (CV)0.1833832289
Kurtosis0.9092734871
Mean103.0772658
Median Absolute Deviation (MAD)12
Skewness0.5224319987
Sum2096076.2
Variance357.3098682
MonotonicityNot monotonic
2021-11-29T11:27:52.420339image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88485
 
2.4%
90461
 
2.3%
97429
 
2.1%
100428
 
2.1%
96424
 
2.1%
91416
 
2.0%
95406
 
2.0%
99404
 
2.0%
93402
 
2.0%
107395
 
1.9%
Other values (246)16085
79.1%
ValueCountFrequency (%)
371
 
< 0.1%
451
 
< 0.1%
482
 
< 0.1%
501
 
< 0.1%
523
< 0.1%
532
 
< 0.1%
545
< 0.1%
555
< 0.1%
565
< 0.1%
56.51
 
< 0.1%
ValueCountFrequency (%)
2801
< 0.1%
2231
< 0.1%
2101
< 0.1%
2011
< 0.1%
2001
< 0.1%
1991
< 0.1%
1931
< 0.1%
1922
< 0.1%
1891
< 0.1%
1881
< 0.1%

O2Sat-min
Real number (ℝ≥0)

Distinct127
Distinct (%)0.6%
Missing12
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean91.99768746
Minimum20
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:52.519894image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile83
Q191
median93
Q395
95-th percentile98
Maximum100
Range80
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.722424054
Coefficient of variation (CV)0.07307166342
Kurtosis34.1866847
Mean91.99768746
Median Absolute Deviation (MAD)2
Skewness-4.824982492
Sum1869761
Variance45.19098516
MonotonicityNot monotonic
2021-11-29T11:27:52.620284image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
942694
13.2%
932566
12.6%
952335
11.5%
922206
10.8%
961734
8.5%
911478
 
7.3%
971112
 
5.5%
901043
 
5.1%
98668
 
3.3%
89625
 
3.1%
Other values (117)3863
19.0%
ValueCountFrequency (%)
202
 
< 0.1%
212
 
< 0.1%
225
< 0.1%
232
 
< 0.1%
242
 
< 0.1%
253
< 0.1%
264
< 0.1%
275
< 0.1%
286
< 0.1%
293
< 0.1%
ValueCountFrequency (%)
100166
 
0.8%
99.515
 
0.1%
99317
 
1.6%
98.527
 
0.1%
98668
 
3.3%
97.541
 
0.2%
971112
5.5%
96.574
 
0.4%
961734
8.5%
95.588
 
0.4%

O2Sat-max
Real number (ℝ≥0)

SKEWED

Distinct35
Distinct (%)0.2%
Missing12
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean99.63535721
Minimum27
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:52.719113image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile98
Q1100
median100
Q3100
95-th percentile100
Maximum100
Range73
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.28680395
Coefficient of variation (CV)0.0129151336
Kurtosis925.7564832
Mean99.63535721
Median Absolute Deviation (MAD)0
Skewness-21.73522171
Sum2024989
Variance1.655864405
MonotonicityNot monotonic
2021-11-29T11:27:52.809078image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
10016312
80.2%
992030
 
10.0%
981025
 
5.0%
97414
 
2.0%
99.5150
 
0.7%
96143
 
0.7%
98.572
 
0.4%
9548
 
0.2%
97.536
 
0.2%
9421
 
0.1%
Other values (25)73
 
0.4%
ValueCountFrequency (%)
271
 
< 0.1%
361
 
< 0.1%
652
< 0.1%
671
 
< 0.1%
713
< 0.1%
761
 
< 0.1%
792
< 0.1%
821
 
< 0.1%
832
< 0.1%
841
 
< 0.1%
ValueCountFrequency (%)
10016312
80.2%
99.5150
 
0.7%
992030
 
10.0%
98.572
 
0.4%
981025
 
5.0%
97.536
 
0.2%
97414
 
2.0%
96.517
 
0.1%
96143
 
0.7%
95.58
 
< 0.1%

Temp-min
Real number (ℝ≥0)

MISSING

Distinct301
Distinct (%)1.5%
Missing235
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean36.06567633
Minimum20.9
Maximum39.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:52.913467image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20.9
5-th percentile35
Q135.67
median36.11
Q336.5
95-th percentile37.11
Maximum39.33
Range18.43
Interquartile range (IQR)0.83

Descriptive statistics

Standard deviation0.7491865947
Coefficient of variation (CV)0.02077284196
Kurtosis36.72512892
Mean36.06567633
Median Absolute Deviation (MAD)0.41
Skewness-2.815209632
Sum724956.16
Variance0.5612805537
MonotonicityNot monotonic
2021-11-29T11:27:53.013649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.111168
 
5.7%
35.56850
 
4.2%
36750
 
3.7%
36.17632
 
3.1%
36.44628
 
3.1%
36.67596
 
2.9%
36.22591
 
2.9%
36.56586
 
2.9%
35.83584
 
2.9%
36.28578
 
2.8%
Other values (291)13138
64.6%
ValueCountFrequency (%)
20.91
 
< 0.1%
211
 
< 0.1%
231
 
< 0.1%
23.61
 
< 0.1%
26.61
 
< 0.1%
26.675
< 0.1%
281
 
< 0.1%
29.61
 
< 0.1%
29.611
 
< 0.1%
29.81
 
< 0.1%
ValueCountFrequency (%)
39.331
< 0.1%
39.171
< 0.1%
39.111
< 0.1%
38.891
< 0.1%
38.831
< 0.1%
38.781
< 0.1%
38.671
< 0.1%
38.612
< 0.1%
38.562
< 0.1%
38.51
< 0.1%

Temp-max
Real number (ℝ≥0)

MISSING

Distinct249
Distinct (%)1.2%
Missing235
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean37.60381872
Minimum30.5
Maximum42.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:53.118870image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30.5
5-th percentile36.56
Q137.11
median37.56
Q338.05
95-th percentile38.89
Maximum42.22
Range11.72
Interquartile range (IQR)0.94

Descriptive statistics

Standard deviation0.7304004107
Coefficient of variation (CV)0.01942357015
Kurtosis1.837707155
Mean37.60381872
Median Absolute Deviation (MAD)0.45
Skewness0.2724133215
Sum755874.36
Variance0.53348476
MonotonicityNot monotonic
2021-11-29T11:27:53.225889image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.67690
 
3.4%
37690
 
3.4%
37.17686
 
3.4%
38665
 
3.3%
37.5653
 
3.2%
37.44627
 
3.1%
37.11570
 
2.8%
37.33561
 
2.8%
37.56545
 
2.7%
36.89538
 
2.6%
Other values (239)13876
68.2%
ValueCountFrequency (%)
30.51
 
< 0.1%
32.61
 
< 0.1%
32.71
 
< 0.1%
33.441
 
< 0.1%
33.52
< 0.1%
33.62
< 0.1%
33.72
< 0.1%
34.251
 
< 0.1%
34.281
 
< 0.1%
34.444
< 0.1%
ValueCountFrequency (%)
42.221
< 0.1%
41.61
< 0.1%
41.441
< 0.1%
41.221
< 0.1%
41.171
< 0.1%
41.112
< 0.1%
411
< 0.1%
40.832
< 0.1%
40.781
< 0.1%
40.611
< 0.1%

SBP-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct357
Distinct (%)1.8%
Missing258
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean95.49430421
Minimum22
Maximum190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:53.327638image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile74
Q186
median93.875
Q3103.5
95-th percentile123
Maximum190
Range168
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation15.27570332
Coefficient of variation (CV)0.1599645492
Kurtosis2.112483679
Mean95.49430421
Median Absolute Deviation (MAD)8.375
Skewness0.5256272955
Sum1917334.64
Variance233.347112
MonotonicityNot monotonic
2021-11-29T11:27:53.422114image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90794
 
3.9%
91695
 
3.4%
92641
 
3.2%
93630
 
3.1%
94606
 
3.0%
95595
 
2.9%
89554
 
2.7%
88530
 
2.6%
97529
 
2.6%
87477
 
2.3%
Other values (347)14027
69.0%
ValueCountFrequency (%)
221
< 0.1%
23.51
< 0.1%
241
< 0.1%
251
< 0.1%
262
< 0.1%
271
< 0.1%
27.51
< 0.1%
282
< 0.1%
292
< 0.1%
301
< 0.1%
ValueCountFrequency (%)
1901
< 0.1%
1871
< 0.1%
1811
< 0.1%
1802
< 0.1%
178.51
< 0.1%
1761
< 0.1%
1741
< 0.1%
1721
< 0.1%
1702
< 0.1%
1691
< 0.1%

SBP-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct392
Distinct (%)2.0%
Missing258
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean147.9312805
Minimum35
Maximum281
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:53.669932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile115.5
Q1132
median146
Q3162
95-th percentile188
Maximum281
Range246
Interquartile range (IQR)30

Descriptive statistics

Standard deviation22.38826445
Coefficient of variation (CV)0.1513423285
Kurtosis0.5512952967
Mean147.9312805
Median Absolute Deviation (MAD)15
Skewness0.5090325192
Sum2970164.25
Variance501.234385
MonotonicityNot monotonic
2021-11-29T11:27:53.770370image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140383
 
1.9%
148367
 
1.8%
142363
 
1.8%
141360
 
1.8%
144355
 
1.7%
138348
 
1.7%
147343
 
1.7%
136341
 
1.7%
137335
 
1.6%
146334
 
1.6%
Other values (382)16549
81.4%
ValueCountFrequency (%)
351
 
< 0.1%
69.51
 
< 0.1%
721
 
< 0.1%
741
 
< 0.1%
752
< 0.1%
75.51
 
< 0.1%
78.51
 
< 0.1%
811
 
< 0.1%
824
< 0.1%
82.251
 
< 0.1%
ValueCountFrequency (%)
2811
< 0.1%
2741
< 0.1%
272.51
< 0.1%
2721
< 0.1%
2501
< 0.1%
2471
< 0.1%
2461
< 0.1%
2452
< 0.1%
2421
< 0.1%
2411
< 0.1%

MAP-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct399
Distinct (%)2.0%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean60.455898
Minimum20
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:53.874128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile43.67
Q154
median60
Q366.67
95-th percentile79
Maximum125
Range105
Interquartile range (IQR)12.67

Descriptive statistics

Standard deviation11.0197621
Coefficient of variation (CV)0.1822777011
Kurtosis1.542480159
Mean60.455898
Median Absolute Deviation (MAD)6
Skewness0.1463582959
Sum1229310.23
Variance121.4351568
MonotonicityNot monotonic
2021-11-29T11:27:53.973751image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60717
 
3.5%
59683
 
3.4%
61666
 
3.3%
57654
 
3.2%
58650
 
3.2%
62611
 
3.0%
63609
 
3.0%
56570
 
2.8%
64547
 
2.7%
55545
 
2.7%
Other values (389)14082
69.2%
ValueCountFrequency (%)
2019
0.1%
20.331
 
< 0.1%
20.52
 
< 0.1%
217
 
< 0.1%
21.331
 
< 0.1%
21.51
 
< 0.1%
2215
0.1%
22.53
 
< 0.1%
2312
0.1%
23.51
 
< 0.1%
ValueCountFrequency (%)
1251
< 0.1%
119.51
< 0.1%
1181
< 0.1%
1171
< 0.1%
1161
< 0.1%
115.51
< 0.1%
114.671
< 0.1%
114.331
< 0.1%
112.671
< 0.1%
111.671
< 0.1%

MAP-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct638
Distinct (%)3.1%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean102.2692102
Minimum22
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:54.070932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile78
Q189
median98.67
Q3110
95-th percentile135
Maximum300
Range278
Interquartile range (IQR)21

Descriptive statistics

Standard deviation22.68689705
Coefficient of variation (CV)0.2218350666
Kurtosis17.90611098
Mean102.2692102
Median Absolute Deviation (MAD)10.66
Skewness3.143988092
Sum2079542.12
Variance514.6952979
MonotonicityNot monotonic
2021-11-29T11:27:54.164821image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
94425
 
2.1%
96422
 
2.1%
93406
 
2.0%
89402
 
2.0%
98401
 
2.0%
88397
 
2.0%
91395
 
1.9%
92391
 
1.9%
95389
 
1.9%
97385
 
1.9%
Other values (628)16321
80.3%
ValueCountFrequency (%)
221
< 0.1%
49.671
< 0.1%
501
< 0.1%
521
< 0.1%
531
< 0.1%
542
< 0.1%
54.331
< 0.1%
551
< 0.1%
562
< 0.1%
57.51
< 0.1%
ValueCountFrequency (%)
3001
 
< 0.1%
2983
< 0.1%
2972
< 0.1%
2954
< 0.1%
2943
< 0.1%
2931
 
< 0.1%
2921
 
< 0.1%
2912
< 0.1%
2902
< 0.1%
2891
 
< 0.1%

DBP-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct172
Distinct (%)1.3%
Missing7384
Missing (%)36.3%
Infinite0
Infinite (%)0.0%
Mean47.79153799
Minimum20
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:54.263977image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile34
Q142
median47
Q353
95-th percentile65
Maximum134
Range114
Interquartile range (IQR)11

Descriptive statistics

Standard deviation9.714343907
Coefficient of variation (CV)0.2032649359
Kurtosis2.265192247
Mean47.79153799
Median Absolute Deviation (MAD)6
Skewness0.7682855006
Sum618996
Variance94.36847754
MonotonicityNot monotonic
2021-11-29T11:27:54.365345image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44598
 
2.9%
48576
 
2.8%
46575
 
2.8%
45567
 
2.8%
47565
 
2.8%
43538
 
2.6%
50531
 
2.6%
49521
 
2.6%
42488
 
2.4%
41452
 
2.2%
Other values (162)7541
37.1%
(Missing)7384
36.3%
ValueCountFrequency (%)
2012
0.1%
20.51
 
< 0.1%
215
 
< 0.1%
21.51
 
< 0.1%
2210
< 0.1%
22.51
 
< 0.1%
2319
0.1%
23.251
 
< 0.1%
2414
0.1%
24.53
 
< 0.1%
ValueCountFrequency (%)
1341
< 0.1%
1171
< 0.1%
1081
< 0.1%
1051
< 0.1%
100.51
< 0.1%
981
< 0.1%
971
< 0.1%
961
< 0.1%
952
< 0.1%
94.51
< 0.1%

DBP-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct265
Distinct (%)2.0%
Missing7384
Missing (%)36.3%
Infinite0
Infinite (%)0.0%
Mean78.33315318
Minimum29
Maximum298
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:54.467156image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile57
Q167
median75
Q386
95-th percentile109
Maximum298
Range269
Interquartile range (IQR)19

Descriptive statistics

Standard deviation18.07409145
Coefficient of variation (CV)0.2307336129
Kurtosis12.44502426
Mean78.33315318
Median Absolute Deviation (MAD)9
Skewness2.199041031
Sum1014571
Variance326.6727816
MonotonicityNot monotonic
2021-11-29T11:27:54.567730image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68376
 
1.8%
70358
 
1.8%
72358
 
1.8%
69358
 
1.8%
73344
 
1.7%
71343
 
1.7%
66333
 
1.6%
74326
 
1.6%
67320
 
1.6%
78317
 
1.6%
Other values (255)9519
46.8%
(Missing)7384
36.3%
ValueCountFrequency (%)
291
< 0.1%
311
< 0.1%
321
< 0.1%
32.751
< 0.1%
341
< 0.1%
361
< 0.1%
36.51
< 0.1%
382
< 0.1%
391
< 0.1%
402
< 0.1%
ValueCountFrequency (%)
2981
< 0.1%
2871
< 0.1%
2721
< 0.1%
2691
< 0.1%
2681
< 0.1%
2671
< 0.1%
2461
< 0.1%
2321
< 0.1%
2221
< 0.1%
2211
< 0.1%

Resp-min
Real number (ℝ≥0)

Distinct82
Distinct (%)0.4%
Missing28
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean12.03610597
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:54.667902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q110
median12
Q314
95-th percentile18
Maximum33
Range32
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.440104721
Coefficient of variation (CV)0.2858154232
Kurtosis1.296419962
Mean12.03610597
Median Absolute Deviation (MAD)2
Skewness0.4076623679
Sum244429.24
Variance11.83432049
MonotonicityNot monotonic
2021-11-29T11:27:54.763985image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
122942
14.5%
102611
12.8%
142085
10.3%
112029
10.0%
131785
8.8%
91375
 
6.8%
151144
 
5.6%
81076
 
5.3%
161024
 
5.0%
7595
 
2.9%
Other values (72)3642
17.9%
ValueCountFrequency (%)
119
 
0.1%
251
 
0.3%
2.51
 
< 0.1%
3100
0.5%
3.53
 
< 0.1%
3.841
 
< 0.1%
4124
0.6%
4.52
 
< 0.1%
5177
0.9%
5.251
 
< 0.1%
ValueCountFrequency (%)
331
 
< 0.1%
321
 
< 0.1%
302
 
< 0.1%
292
 
< 0.1%
28.51
 
< 0.1%
2810
< 0.1%
275
 
< 0.1%
26.51
 
< 0.1%
2616
0.1%
25.51
 
< 0.1%

Resp-max
Real number (ℝ≥0)

Distinct131
Distinct (%)0.6%
Missing28
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean27.01727152
Minimum9.5
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:54.864157image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum9.5
5-th percentile19
Q123
median26
Q330
95-th percentile39
Maximum69
Range59.5
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.405685686
Coefficient of variation (CV)0.2370959511
Kurtosis3.699797033
Mean27.01727152
Median Absolute Deviation (MAD)4
Skewness1.3589424
Sum548666.75
Variance41.03280911
MonotonicityNot monotonic
2021-11-29T11:27:54.960185image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
241604
 
7.9%
251529
 
7.5%
221394
 
6.9%
261388
 
6.8%
231383
 
6.8%
271264
 
6.2%
281249
 
6.1%
29971
 
4.8%
21960
 
4.7%
20906
 
4.5%
Other values (121)7660
37.7%
ValueCountFrequency (%)
9.51
 
< 0.1%
105
 
< 0.1%
127
 
< 0.1%
133
 
< 0.1%
13.53
 
< 0.1%
13.751
 
< 0.1%
1441
0.2%
14.251
 
< 0.1%
14.58
 
< 0.1%
1537
0.2%
ValueCountFrequency (%)
693
 
< 0.1%
677
< 0.1%
662
 
< 0.1%
65.51
 
< 0.1%
655
< 0.1%
646
< 0.1%
634
 
< 0.1%
621
 
< 0.1%
613
 
< 0.1%
6011
0.1%

EtCO2-min
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing20336
Missing (%)100.0%
Memory size159.0 KiB

EtCO2-max
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing20336
Missing (%)100.0%
Memory size159.0 KiB

BaseExcess-min
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct85
Distinct (%)0.7%
Missing7684
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean-2.297344293
Minimum-32
Maximum25
Zeros2278
Zeros (%)11.2%
Negative8125
Negative (%)40.0%
Memory size159.0 KiB
2021-11-29T11:27:55.061864image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-32
5-th percentile-10
Q1-4.5
median-2
Q30
95-th percentile4
Maximum25
Range57
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation4.570432573
Coefficient of variation (CV)-1.989441716
Kurtosis4.146076782
Mean-2.297344293
Median Absolute Deviation (MAD)2
Skewness-0.6375875951
Sum-29066
Variance20.88885391
MonotonicityNot monotonic
2021-11-29T11:27:55.237459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02278
 
11.2%
-21337
 
6.6%
-31254
 
6.2%
-11240
 
6.1%
-41009
 
5.0%
-5823
 
4.0%
-6614
 
3.0%
1586
 
2.9%
2455
 
2.2%
-7422
 
2.1%
Other values (75)2634
 
13.0%
(Missing)7684
37.8%
ValueCountFrequency (%)
-321
 
< 0.1%
-301
 
< 0.1%
-292
 
< 0.1%
-282
 
< 0.1%
-275
< 0.1%
-26.51
 
< 0.1%
-264
< 0.1%
-25.51
 
< 0.1%
-257
< 0.1%
-249
< 0.1%
ValueCountFrequency (%)
251
 
< 0.1%
231
 
< 0.1%
211
 
< 0.1%
201
 
< 0.1%
192
 
< 0.1%
183
 
< 0.1%
175
< 0.1%
1610
< 0.1%
155
< 0.1%
148
< 0.1%

BaseExcess-max
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct75
Distinct (%)0.6%
Missing7684
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean1.436452735
Minimum-25
Maximum100
Zeros3101
Zeros (%)15.2%
Negative2732
Negative (%)13.4%
Memory size159.0 KiB
2021-11-29T11:27:55.337147image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-25
5-th percentile-4
Q10
median1
Q33
95-th percentile8
Maximum100
Range125
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.132239319
Coefficient of variation (CV)2.876697032
Kurtosis31.99474638
Mean1.436452735
Median Absolute Deviation (MAD)2
Skewness1.690405242
Sum18174
Variance17.07540179
MonotonicityNot monotonic
2021-11-29T11:27:55.441290image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
03101
15.2%
11478
 
7.3%
21232
 
6.1%
31100
 
5.4%
-1852
 
4.2%
4847
 
4.2%
-2598
 
2.9%
5566
 
2.8%
6436
 
2.1%
-3410
 
2.0%
Other values (65)2032
 
10.0%
(Missing)7684
37.8%
ValueCountFrequency (%)
-251
 
< 0.1%
-242
 
< 0.1%
-212
 
< 0.1%
-201
 
< 0.1%
-196
< 0.1%
-18.51
 
< 0.1%
-181
 
< 0.1%
-174
< 0.1%
-168
< 0.1%
-157
< 0.1%
ValueCountFrequency (%)
1001
 
< 0.1%
49.51
 
< 0.1%
441
 
< 0.1%
361
 
< 0.1%
281
 
< 0.1%
262
 
< 0.1%
252
 
< 0.1%
247
< 0.1%
232
 
< 0.1%
224
< 0.1%

HCO3-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct57
Distinct (%)0.3%
Missing535
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean23.17581183
Minimum0
Maximum53
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:55.542485image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16
Q121
median23
Q326
95-th percentile30
Maximum53
Range53
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.273794163
Coefficient of variation (CV)0.1844075277
Kurtosis2.619759907
Mean23.17581183
Median Absolute Deviation (MAD)2
Skewness0.04733510069
Sum458904.25
Variance18.26531654
MonotonicityNot monotonic
2021-11-29T11:27:55.643002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
242384
11.7%
232362
11.6%
222120
10.4%
251993
9.8%
211625
8.0%
261589
7.8%
201250
 
6.1%
271146
 
5.6%
19894
 
4.4%
28711
 
3.5%
Other values (47)3727
18.3%
ValueCountFrequency (%)
02
 
< 0.1%
510
 
< 0.1%
617
 
0.1%
79
 
< 0.1%
831
 
0.2%
931
 
0.2%
1050
0.2%
10.51
 
< 0.1%
1163
0.3%
1283
0.4%
ValueCountFrequency (%)
531
 
< 0.1%
502
 
< 0.1%
472
 
< 0.1%
462
 
< 0.1%
454
 
< 0.1%
444
 
< 0.1%
437
 
< 0.1%
429
< 0.1%
418
< 0.1%
4018
0.1%

HCO3-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct58
Distinct (%)0.3%
Missing535
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean25.60966618
Minimum5
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:55.739698image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile20
Q123
median25
Q328
95-th percentile32
Maximum55
Range50
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.008038702
Coefficient of variation (CV)0.1565049179
Kurtosis2.941087155
Mean25.60966618
Median Absolute Deviation (MAD)2
Skewness0.5302548319
Sum507097
Variance16.06437424
MonotonicityNot monotonic
2021-11-29T11:27:55.837623image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
252511
12.3%
262350
11.6%
242200
10.8%
272089
10.3%
231840
9.0%
281569
7.7%
221229
 
6.0%
291189
 
5.8%
30780
 
3.8%
21765
 
3.8%
Other values (48)3279
16.1%
ValueCountFrequency (%)
51
 
< 0.1%
61
 
< 0.1%
72
 
< 0.1%
84
 
< 0.1%
95
 
< 0.1%
109
 
< 0.1%
119
 
< 0.1%
1212
0.1%
1323
0.1%
1427
0.1%
ValueCountFrequency (%)
551
 
< 0.1%
521
 
< 0.1%
503
 
< 0.1%
494
 
< 0.1%
482
 
< 0.1%
474
 
< 0.1%
464
 
< 0.1%
459
< 0.1%
4410
< 0.1%
4313
0.1%

FiO2-min
Real number (ℝ≥0)

MISSING

Distinct68
Distinct (%)0.6%
Missing8349
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean0.4424851923
Minimum0
Maximum10
Zeros64
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:55.937493image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q10.4
median0.4
Q30.5
95-th percentile0.7
Maximum10
Range10
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.162033493
Coefficient of variation (CV)0.3661896393
Kurtosis1012.647919
Mean0.4424851923
Median Absolute Deviation (MAD)0.05
Skewness18.14424911
Sum5304.07
Variance0.02625485284
MonotonicityNot monotonic
2021-11-29T11:27:56.036290image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.45904
29.0%
0.53221
 
15.8%
0.35904
 
4.4%
0.3368
 
1.8%
1312
 
1.5%
0.6283
 
1.4%
0.7178
 
0.9%
0.45122
 
0.6%
0.2195
 
0.5%
064
 
0.3%
Other values (58)536
 
2.6%
(Missing)8349
41.1%
ValueCountFrequency (%)
064
0.3%
0.0233
0.2%
0.0322
 
0.1%
0.0446
0.2%
0.0511
 
0.1%
0.062
 
< 0.1%
0.083
 
< 0.1%
0.13
 
< 0.1%
0.112
 
< 0.1%
0.122
 
< 0.1%
ValueCountFrequency (%)
101
 
< 0.1%
1312
1.5%
0.993
 
< 0.1%
0.986
 
< 0.1%
0.962
 
< 0.1%
0.9539
 
0.2%
0.941
 
< 0.1%
0.931
 
< 0.1%
0.921
 
< 0.1%
0.912
 
< 0.1%

FiO2-max
Real number (ℝ≥0)

MISSING

Distinct64
Distinct (%)0.5%
Missing8349
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean0.7496262618
Minimum0
Maximum10
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:56.137869image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q10.5
median0.75
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.2671071528
Coefficient of variation (CV)0.3563204311
Kurtosis143.161105
Mean0.7496262618
Median Absolute Deviation (MAD)0.25
Skewness4.350642728
Sum8985.77
Variance0.07134623107
MonotonicityNot monotonic
2021-11-29T11:27:56.236146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15219
25.7%
0.52676
 
13.2%
0.41065
 
5.2%
0.6820
 
4.0%
0.7758
 
3.7%
0.8386
 
1.9%
0.75315
 
1.5%
0.35165
 
0.8%
0.9594
 
0.5%
0.973
 
0.4%
Other values (54)416
 
2.0%
(Missing)8349
41.1%
ValueCountFrequency (%)
02
 
< 0.1%
0.022
 
< 0.1%
0.033
 
< 0.1%
0.044
 
< 0.1%
0.081
 
< 0.1%
0.111
 
< 0.1%
0.230
0.1%
0.2135
0.2%
0.221
 
< 0.1%
0.245
 
< 0.1%
ValueCountFrequency (%)
101
 
< 0.1%
71
 
< 0.1%
15219
25.7%
0.999
 
< 0.1%
0.989
 
< 0.1%
0.975
 
< 0.1%
0.964
 
< 0.1%
0.9594
 
0.5%
0.942
 
< 0.1%
0.931
 
< 0.1%

pH-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct84
Distinct (%)0.6%
Missing7155
Missing (%)35.2%
Infinite0
Infinite (%)0.0%
Mean7.335895607
Minimum6.62
Maximum7.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:56.336822image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.62
5-th percentile7.2
Q17.3
median7.34
Q37.39
95-th percentile7.45
Maximum7.73
Range1.11
Interquartile range (IQR)0.09

Descriptive statistics

Standard deviation0.08094798361
Coefficient of variation (CV)0.01103450593
Kurtosis4.900062879
Mean7.335895607
Median Absolute Deviation (MAD)0.05
Skewness-1.212676517
Sum96694.44
Variance0.006552576051
MonotonicityNot monotonic
2021-11-29T11:27:56.433184image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.36819
 
4.0%
7.35798
 
3.9%
7.34797
 
3.9%
7.32758
 
3.7%
7.37746
 
3.7%
7.33744
 
3.7%
7.31667
 
3.3%
7.38662
 
3.3%
7.4597
 
2.9%
7.39579
 
2.8%
Other values (74)6014
29.6%
(Missing)7155
35.2%
ValueCountFrequency (%)
6.621
 
< 0.1%
6.631
 
< 0.1%
6.651
 
< 0.1%
6.781
 
< 0.1%
6.791
 
< 0.1%
6.811
 
< 0.1%
6.823
< 0.1%
6.853
< 0.1%
6.865
< 0.1%
6.873
< 0.1%
ValueCountFrequency (%)
7.731
 
< 0.1%
7.661
 
< 0.1%
7.631
 
< 0.1%
7.591
 
< 0.1%
7.571
 
< 0.1%
7.562
 
< 0.1%
7.558
 
< 0.1%
7.546
 
< 0.1%
7.5313
0.1%
7.5222
0.1%

pH-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct80
Distinct (%)0.6%
Missing7155
Missing (%)35.2%
Infinite0
Infinite (%)0.0%
Mean7.426962294
Minimum6.63
Maximum7.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:56.529586image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.63
5-th percentile7.33
Q17.39
median7.43
Q37.47
95-th percentile7.52
Maximum7.93
Range1.3
Interquartile range (IQR)0.08

Descriptive statistics

Standard deviation0.06352993288
Coefficient of variation (CV)0.008553959259
Kurtosis7.746723601
Mean7.426962294
Median Absolute Deviation (MAD)0.04
Skewness-0.9298301191
Sum97894.79
Variance0.004036052372
MonotonicityNot monotonic
2021-11-29T11:27:56.632931image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.421013
 
5.0%
7.44986
 
4.8%
7.43957
 
4.7%
7.45912
 
4.5%
7.4869
 
4.3%
7.41869
 
4.3%
7.46801
 
3.9%
7.39736
 
3.6%
7.47671
 
3.3%
7.48645
 
3.2%
Other values (70)4722
23.2%
(Missing)7155
35.2%
ValueCountFrequency (%)
6.631
 
< 0.1%
6.651
 
< 0.1%
6.871
 
< 0.1%
6.941
 
< 0.1%
6.983
< 0.1%
72
< 0.1%
7.011
 
< 0.1%
7.021
 
< 0.1%
7.032
< 0.1%
7.051
 
< 0.1%
ValueCountFrequency (%)
7.931
 
< 0.1%
7.81
 
< 0.1%
7.781
 
< 0.1%
7.731
 
< 0.1%
7.721
 
< 0.1%
7.711
 
< 0.1%
7.692
< 0.1%
7.681
 
< 0.1%
7.671
 
< 0.1%
7.663
< 0.1%

PaCO2-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct117
Distinct (%)0.9%
Missing7759
Missing (%)38.2%
Infinite0
Infinite (%)0.0%
Mean36.58972728
Minimum10
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:56.818856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile26
Q132
median36
Q340
95-th percentile49
Maximum95
Range85
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.834064984
Coefficient of variation (CV)0.2141055855
Kurtosis5.448878524
Mean36.58972728
Median Absolute Deviation (MAD)4
Skewness1.335619828
Sum460189
Variance61.37257417
MonotonicityNot monotonic
2021-11-29T11:27:56.915371image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36817
 
4.0%
35785
 
3.9%
34781
 
3.8%
37759
 
3.7%
38750
 
3.7%
33711
 
3.5%
32703
 
3.5%
39605
 
3.0%
31592
 
2.9%
40589
 
2.9%
Other values (107)5485
27.0%
(Missing)7759
38.2%
ValueCountFrequency (%)
101
 
< 0.1%
113
 
< 0.1%
122
 
< 0.1%
132
 
< 0.1%
144
 
< 0.1%
156
 
< 0.1%
1610
< 0.1%
16.51
 
< 0.1%
1714
0.1%
1815
0.1%
ValueCountFrequency (%)
951
 
< 0.1%
942
< 0.1%
931
 
< 0.1%
89.51
 
< 0.1%
891
 
< 0.1%
881
 
< 0.1%
872
< 0.1%
863
< 0.1%
852
< 0.1%
842
< 0.1%

PaCO2-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct131
Distinct (%)1.0%
Missing7759
Missing (%)38.2%
Infinite0
Infinite (%)0.0%
Mean46.35227002
Minimum10
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:57.016523image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile33
Q140
median45
Q350
95-th percentile64
Maximum100
Range90
Interquartile range (IQR)10

Descriptive statistics

Standard deviation10.12168536
Coefficient of variation (CV)0.2183643941
Kurtosis4.864624124
Mean46.35227002
Median Absolute Deviation (MAD)5
Skewness1.558116938
Sum582972.5
Variance102.4485144
MonotonicityNot monotonic
2021-11-29T11:27:57.113404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46715
 
3.5%
44686
 
3.4%
42676
 
3.3%
43659
 
3.2%
47620
 
3.0%
45616
 
3.0%
40601
 
3.0%
41567
 
2.8%
48549
 
2.7%
49511
 
2.5%
Other values (121)6377
31.4%
(Missing)7759
38.2%
ValueCountFrequency (%)
101
 
< 0.1%
162
 
< 0.1%
191
 
< 0.1%
208
 
< 0.1%
215
 
< 0.1%
228
 
< 0.1%
2314
0.1%
247
 
< 0.1%
2519
0.1%
2628
0.1%
ValueCountFrequency (%)
10010
< 0.1%
996
< 0.1%
984
 
< 0.1%
97.51
 
< 0.1%
9710
< 0.1%
964
 
< 0.1%
95.51
 
< 0.1%
954
 
< 0.1%
94.51
 
< 0.1%
9412
0.1%

SaO2-min
Real number (ℝ≥0)

MISSING

Distinct116
Distinct (%)1.5%
Missing12373
Missing (%)60.8%
Infinite0
Infinite (%)0.0%
Mean84.27638453
Minimum24
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:57.213554image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile54
Q171
median94
Q397
95-th percentile98
Maximum100
Range76
Interquartile range (IQR)26

Descriptive statistics

Standard deviation16.0983399
Coefficient of variation (CV)0.1910183973
Kurtosis-0.4464067556
Mean84.27638453
Median Absolute Deviation (MAD)4
Skewness-0.9075627908
Sum671092.85
Variance259.1565476
MonotonicityNot monotonic
2021-11-29T11:27:57.309876image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
981307
 
6.4%
971045
 
5.1%
96689
 
3.4%
95404
 
2.0%
94319
 
1.6%
99309
 
1.5%
93195
 
1.0%
92140
 
0.7%
63128
 
0.6%
67120
 
0.6%
Other values (106)3307
 
16.3%
(Missing)12373
60.8%
ValueCountFrequency (%)
241
 
< 0.1%
261
 
< 0.1%
272
< 0.1%
281
 
< 0.1%
293
< 0.1%
304
< 0.1%
311
 
< 0.1%
322
< 0.1%
331
 
< 0.1%
33.51
 
< 0.1%
ValueCountFrequency (%)
10018
 
0.1%
99309
 
1.5%
98.52
 
< 0.1%
981307
6.4%
97.59
 
< 0.1%
971045
5.1%
96.58
 
< 0.1%
96689
3.4%
95.56
 
< 0.1%
95.41
 
< 0.1%

SaO2-max
Real number (ℝ≥0)

MISSING

Distinct81
Distinct (%)1.0%
Missing12373
Missing (%)60.8%
Infinite0
Infinite (%)0.0%
Mean95.64866256
Minimum30
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:57.412457image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile77
Q197
median98
Q399
95-th percentile99
Maximum100
Range70
Interquartile range (IQR)2

Descriptive statistics

Standard deviation7.480275942
Coefficient of variation (CV)0.07820575574
Kurtosis13.82734097
Mean95.64866256
Median Absolute Deviation (MAD)1
Skewness-3.586364209
Sum761650.3
Variance55.95452817
MonotonicityNot monotonic
2021-11-29T11:27:57.510529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
983130
 
15.4%
991929
 
9.5%
971074
 
5.3%
96430
 
2.1%
95195
 
1.0%
100159
 
0.8%
94109
 
0.5%
9367
 
0.3%
9248
 
0.2%
7137
 
0.2%
Other values (71)785
 
3.9%
(Missing)12373
60.8%
ValueCountFrequency (%)
302
 
< 0.1%
341
 
< 0.1%
402
 
< 0.1%
421
 
< 0.1%
431
 
< 0.1%
441
 
< 0.1%
461
 
< 0.1%
495
< 0.1%
502
 
< 0.1%
511
 
< 0.1%
ValueCountFrequency (%)
100159
 
0.8%
99.52
 
< 0.1%
99.31
 
< 0.1%
991929
9.5%
98.530
 
0.1%
983130
15.4%
97.519
 
0.1%
971074
 
5.3%
96.54
 
< 0.1%
96430
 
2.1%

AST-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct653
Distinct (%)11.1%
Missing14443
Missing (%)71.0%
Infinite0
Infinite (%)0.0%
Mean134.0123027
Minimum3
Maximum9210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:57.614918image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile13
Q122
median39
Q386
95-th percentile458.8
Maximum9210
Range9207
Interquartile range (IQR)64

Descriptive statistics

Standard deviation434.3887697
Coefficient of variation (CV)3.241409638
Kurtosis136.1199603
Mean134.0123027
Median Absolute Deviation (MAD)21
Skewness10.11325823
Sum789734.5
Variance188693.6033
MonotonicityNot monotonic
2021-11-29T11:27:57.711930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17162
 
0.8%
18151
 
0.7%
19142
 
0.7%
24139
 
0.7%
16133
 
0.7%
23127
 
0.6%
15126
 
0.6%
21123
 
0.6%
20122
 
0.6%
22122
 
0.6%
Other values (643)4546
 
22.4%
(Missing)14443
71.0%
ValueCountFrequency (%)
32
 
< 0.1%
41
 
< 0.1%
52
 
< 0.1%
5.51
 
< 0.1%
66
 
< 0.1%
76
 
< 0.1%
818
 
0.1%
920
 
0.1%
1042
0.2%
1155
0.3%
ValueCountFrequency (%)
92101
< 0.1%
85911
< 0.1%
71741
< 0.1%
68841
< 0.1%
67131
< 0.1%
60001
< 0.1%
58971
< 0.1%
54351
< 0.1%
53591
< 0.1%
53311
< 0.1%

AST-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct853
Distinct (%)14.5%
Missing14443
Missing (%)71.0%
Infinite0
Infinite (%)0.0%
Mean246.5676226
Minimum3
Maximum9890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:57.813026image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile14
Q124
median45
Q3107
95-th percentile870.8
Maximum9890
Range9887
Interquartile range (IQR)83

Descriptive statistics

Standard deviation895.2502488
Coefficient of variation (CV)3.630850796
Kurtosis59.17982982
Mean246.5676226
Median Absolute Deviation (MAD)26
Skewness7.255823541
Sum1453023
Variance801473.0079
MonotonicityNot monotonic
2021-11-29T11:27:57.913664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19137
 
0.7%
18127
 
0.6%
16125
 
0.6%
17122
 
0.6%
21120
 
0.6%
20119
 
0.6%
24119
 
0.6%
22117
 
0.6%
23105
 
0.5%
15105
 
0.5%
Other values (843)4697
 
23.1%
(Missing)14443
71.0%
ValueCountFrequency (%)
32
 
< 0.1%
41
 
< 0.1%
51
 
< 0.1%
65
 
< 0.1%
75
 
< 0.1%
810
 
< 0.1%
915
 
0.1%
1036
0.2%
1147
0.2%
1257
0.3%
ValueCountFrequency (%)
98901
< 0.1%
98401
< 0.1%
97301
< 0.1%
96401
< 0.1%
95071
< 0.1%
94951
< 0.1%
94901
< 0.1%
94561
< 0.1%
94301
< 0.1%
92481
< 0.1%

BUN-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct154
Distinct (%)0.8%
Missing427
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean20.25654227
Minimum1
Maximum184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:58.013944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q111
median15
Q323
95-th percentile54
Maximum184
Range183
Interquartile range (IQR)12

Descriptive statistics

Standard deviation16.83914067
Coefficient of variation (CV)0.8312939322
Kurtosis10.91226427
Mean20.25654227
Median Absolute Deviation (MAD)6
Skewness2.789987005
Sum403287.5
Variance283.5566586
MonotonicityNot monotonic
2021-11-29T11:27:58.114212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
111143
 
5.6%
121115
 
5.5%
131106
 
5.4%
141080
 
5.3%
101076
 
5.3%
9992
 
4.9%
15965
 
4.7%
8829
 
4.1%
16821
 
4.0%
17794
 
3.9%
Other values (144)9988
49.1%
ValueCountFrequency (%)
110
 
< 0.1%
248
 
0.2%
2.51
 
< 0.1%
3142
 
0.7%
4213
 
1.0%
5385
 
1.9%
6541
2.7%
7734
3.6%
8829
4.1%
9992
4.9%
ValueCountFrequency (%)
1841
< 0.1%
1701
< 0.1%
1691
< 0.1%
1651
< 0.1%
1621
< 0.1%
1601
< 0.1%
1591
< 0.1%
1551
< 0.1%
1491
< 0.1%
1481
< 0.1%

BUN-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct169
Distinct (%)0.8%
Missing427
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean25.02549098
Minimum2
Maximum266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:58.220562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8
Q113
median19
Q329
95-th percentile66
Maximum266
Range264
Interquartile range (IQR)16

Descriptive statistics

Standard deviation20.14009704
Coefficient of variation (CV)0.8047832929
Kurtosis10.20048738
Mean25.02549098
Median Absolute Deviation (MAD)7
Skewness2.648994795
Sum498232.5
Variance405.6235088
MonotonicityNot monotonic
2021-11-29T11:27:58.402756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14991
 
4.9%
15976
 
4.8%
13953
 
4.7%
16924
 
4.5%
12902
 
4.4%
17881
 
4.3%
11826
 
4.1%
10776
 
3.8%
18758
 
3.7%
19727
 
3.6%
Other values (159)11195
55.1%
ValueCountFrequency (%)
28
 
< 0.1%
337
 
0.2%
481
 
0.4%
5132
 
0.6%
6242
 
1.2%
7358
1.8%
8483
2.4%
9616
3.0%
10776
3.8%
11826
4.1%
ValueCountFrequency (%)
2661
 
< 0.1%
2351
 
< 0.1%
2051
 
< 0.1%
2011
 
< 0.1%
1951
 
< 0.1%
1843
< 0.1%
1741
 
< 0.1%
1711
 
< 0.1%
1702
< 0.1%
1691
 
< 0.1%

Alkalinephos-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct455
Distinct (%)8.0%
Missing14633
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean104.7543398
Minimum7
Maximum3619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:58.501114image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile36
Q155
median75
Q3110
95-th percentile258.9
Maximum3619
Range3612
Interquartile range (IQR)55

Descriptive statistics

Standard deviation123.7548782
Coefficient of variation (CV)1.181381873
Kurtosis184.422028
Mean104.7543398
Median Absolute Deviation (MAD)24
Skewness9.984337255
Sum597414
Variance15315.26988
MonotonicityNot monotonic
2021-11-29T11:27:58.599756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5881
 
0.4%
4979
 
0.4%
5578
 
0.4%
5277
 
0.4%
5976
 
0.4%
7276
 
0.4%
6076
 
0.4%
5075
 
0.4%
5675
 
0.4%
6875
 
0.4%
Other values (445)4935
 
24.3%
(Missing)14633
72.0%
ValueCountFrequency (%)
71
 
< 0.1%
111
 
< 0.1%
121
 
< 0.1%
131
 
< 0.1%
142
< 0.1%
152
< 0.1%
161
 
< 0.1%
172
< 0.1%
184
< 0.1%
192
< 0.1%
ValueCountFrequency (%)
36191
< 0.1%
25281
< 0.1%
21011
< 0.1%
19191
< 0.1%
17761
< 0.1%
16691
< 0.1%
14371
< 0.1%
14361
< 0.1%
11651
< 0.1%
11551
< 0.1%

Alkalinephos-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct491
Distinct (%)8.6%
Missing14633
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean114.4879888
Minimum7
Maximum3833
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:58.706676image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile38
Q158
median79
Q3119
95-th percentile297
Maximum3833
Range3826
Interquartile range (IQR)61

Descriptive statistics

Standard deviation140.5028521
Coefficient of variation (CV)1.227227883
Kurtosis150.3540625
Mean114.4879888
Median Absolute Deviation (MAD)26
Skewness9.156134551
Sum652925
Variance19741.05146
MonotonicityNot monotonic
2021-11-29T11:27:58.810478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5592
 
0.5%
6080
 
0.4%
5980
 
0.4%
6779
 
0.4%
4977
 
0.4%
7375
 
0.4%
7275
 
0.4%
5874
 
0.4%
6974
 
0.4%
6172
 
0.4%
Other values (481)4925
 
24.2%
(Missing)14633
72.0%
ValueCountFrequency (%)
71
 
< 0.1%
121
 
< 0.1%
151
 
< 0.1%
171
 
< 0.1%
181
 
< 0.1%
191
 
< 0.1%
202
< 0.1%
211
 
< 0.1%
223
< 0.1%
234
< 0.1%
ValueCountFrequency (%)
38331
< 0.1%
25281
< 0.1%
24401
< 0.1%
21901
< 0.1%
21211
< 0.1%
17991
< 0.1%
16691
< 0.1%
15461
< 0.1%
15011
< 0.1%
14371
< 0.1%

Calcium-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct92
Distinct (%)0.6%
Missing3789
Missing (%)18.6%
Infinite0
Infinite (%)0.0%
Mean8.144180214
Minimum1.6
Maximum15.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:58.916064image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1.6
5-th percentile6.9
Q17.7
median8.2
Q38.6
95-th percentile9.3
Maximum15.7
Range14.1
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.7700559677
Coefficient of variation (CV)0.09455291354
Kurtosis3.578194828
Mean8.144180214
Median Absolute Deviation (MAD)0.5
Skewness-0.1429625023
Sum134761.75
Variance0.5929861933
MonotonicityNot monotonic
2021-11-29T11:27:59.013252image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.31005
 
4.9%
8.2971
 
4.8%
8.1968
 
4.8%
8.4952
 
4.7%
8.5908
 
4.5%
8885
 
4.4%
7.9854
 
4.2%
8.6852
 
4.2%
7.8779
 
3.8%
7.7763
 
3.8%
Other values (82)7610
37.4%
(Missing)3789
18.6%
ValueCountFrequency (%)
1.61
< 0.1%
2.82
< 0.1%
3.51
< 0.1%
3.61
< 0.1%
3.71
< 0.1%
3.91
< 0.1%
4.21
< 0.1%
4.32
< 0.1%
4.52
< 0.1%
4.61
< 0.1%
ValueCountFrequency (%)
15.71
< 0.1%
15.41
< 0.1%
13.61
< 0.1%
13.11
< 0.1%
12.91
< 0.1%
12.71
< 0.1%
12.42
< 0.1%
12.21
< 0.1%
11.71
< 0.1%
11.61
< 0.1%

Calcium-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct109
Distinct (%)0.7%
Missing3789
Missing (%)18.6%
Infinite0
Infinite (%)0.0%
Mean8.549410769
Minimum3.9
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:59.118546image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3.9
5-th percentile7.5
Q18.1
median8.5
Q38.9
95-th percentile9.7
Maximum22
Range18.1
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.7765680555
Coefficient of variation (CV)0.09083293299
Kurtosis22.34361276
Mean8.549410769
Median Absolute Deviation (MAD)0.4
Skewness2.087220841
Sum141467.1
Variance0.6030579448
MonotonicityNot monotonic
2021-11-29T11:27:59.219740image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.51107
 
5.4%
8.61054
 
5.2%
8.41032
 
5.1%
8.31018
 
5.0%
8.2975
 
4.8%
8.7961
 
4.7%
8.8922
 
4.5%
8.1859
 
4.2%
8.9799
 
3.9%
9747
 
3.7%
Other values (99)7073
34.8%
(Missing)3789
18.6%
ValueCountFrequency (%)
3.91
 
< 0.1%
4.51
 
< 0.1%
4.72
< 0.1%
5.33
< 0.1%
5.41
 
< 0.1%
5.51
 
< 0.1%
5.62
< 0.1%
5.71
 
< 0.1%
5.82
< 0.1%
5.91
 
< 0.1%
ValueCountFrequency (%)
221
< 0.1%
21.51
< 0.1%
19.61
< 0.1%
19.21
< 0.1%
171
< 0.1%
16.21
< 0.1%
15.71
< 0.1%
15.61
< 0.1%
15.42
< 0.1%
15.31
< 0.1%

Chloride-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct71
Distinct (%)0.4%
Missing542
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean103.8362888
Minimum26
Maximum137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:59.330789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile95
Q1101
median104
Q3107
95-th percentile112
Maximum137
Range111
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.324223637
Coefficient of variation (CV)0.05127517268
Kurtosis5.398835036
Mean103.8362888
Median Absolute Deviation (MAD)3
Skewness-0.6879826935
Sum2055335.5
Variance28.34735734
MonotonicityNot monotonic
2021-11-29T11:27:59.425168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1051748
 
8.6%
1041687
 
8.3%
1061644
 
8.1%
1031619
 
8.0%
1071480
 
7.3%
1021413
 
6.9%
1011212
 
6.0%
1081178
 
5.8%
1001043
 
5.1%
109997
 
4.9%
Other values (61)5773
28.4%
ValueCountFrequency (%)
261
 
< 0.1%
381
 
< 0.1%
631
 
< 0.1%
661
 
< 0.1%
701
 
< 0.1%
732
< 0.1%
741
 
< 0.1%
753
< 0.1%
763
< 0.1%
783
< 0.1%
ValueCountFrequency (%)
1371
 
< 0.1%
1331
 
< 0.1%
1321
 
< 0.1%
1311
 
< 0.1%
1302
 
< 0.1%
1291
 
< 0.1%
1282
 
< 0.1%
1272
 
< 0.1%
1252
 
< 0.1%
1246
< 0.1%

Chloride-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct65
Distinct (%)0.3%
Missing542
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean107.1987724
Minimum73
Maximum145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:59.524058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum73
5-th percentile98
Q1104
median107
Q3111
95-th percentile116
Maximum145
Range72
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.611802707
Coefficient of variation (CV)0.05234950535
Kurtosis1.798068267
Mean107.1987724
Median Absolute Deviation (MAD)3
Skewness0.07079333277
Sum2121892.5
Variance31.49232962
MonotonicityNot monotonic
2021-11-29T11:27:59.622844image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1081599
 
7.9%
1071569
 
7.7%
1091501
 
7.4%
1061487
 
7.3%
1101390
 
6.8%
1051333
 
6.6%
1041185
 
5.8%
1111162
 
5.7%
103994
 
4.9%
112967
 
4.8%
Other values (55)6607
32.5%
ValueCountFrequency (%)
731
 
< 0.1%
741
 
< 0.1%
802
 
< 0.1%
811
 
< 0.1%
821
 
< 0.1%
834
 
< 0.1%
841
 
< 0.1%
852
 
< 0.1%
865
< 0.1%
8711
0.1%
ValueCountFrequency (%)
1451
 
< 0.1%
1411
 
< 0.1%
1402
 
< 0.1%
1394
< 0.1%
1376
< 0.1%
1354
< 0.1%
1341
 
< 0.1%
1331
 
< 0.1%
1325
< 0.1%
1318
< 0.1%

Creatinine-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct133
Distinct (%)0.7%
Missing461
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean1.184792453
Minimum0.1
Maximum25.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:27:59.727689image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.4
Q10.6
median0.8
Q31.1
95-th percentile3.5
Maximum25.1
Range25
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation1.28246168
Coefficient of variation (CV)1.082435727
Kurtosis31.24324077
Mean1.184792453
Median Absolute Deviation (MAD)0.2
Skewness4.637918015
Sum23547.75
Variance1.644707961
MonotonicityNot monotonic
2021-11-29T11:27:59.828995image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.72837
14.0%
0.82572
12.6%
0.62410
11.9%
0.91898
9.3%
0.51735
8.5%
11401
 
6.9%
1.1959
 
4.7%
0.4838
 
4.1%
1.2745
 
3.7%
1.3546
 
2.7%
Other values (123)3934
19.3%
(Missing)461
 
2.3%
ValueCountFrequency (%)
0.118
 
0.1%
0.268
 
0.3%
0.3255
 
1.3%
0.4838
 
4.1%
0.51735
8.5%
0.62410
11.9%
0.72837
14.0%
0.752
 
< 0.1%
0.82572
12.6%
0.91898
9.3%
ValueCountFrequency (%)
25.11
< 0.1%
17.61
< 0.1%
17.31
< 0.1%
16.51
< 0.1%
15.71
< 0.1%
15.61
< 0.1%
14.71
< 0.1%
14.21
< 0.1%
13.82
< 0.1%
13.71
< 0.1%

Creatinine-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct156
Distinct (%)0.8%
Missing461
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean1.416528302
Minimum0.1
Maximum46.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:00.011396image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.5
Q10.7
median0.9
Q31.3
95-th percentile4.4
Maximum46.6
Range46.5
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation1.60387656
Coefficient of variation (CV)1.132258747
Kurtosis55.75782003
Mean1.416528302
Median Absolute Deviation (MAD)0.2
Skewness5.189413788
Sum28153.5
Variance2.572420019
MonotonicityNot monotonic
2021-11-29T11:28:00.108440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.82498
12.3%
0.72343
11.5%
0.92179
10.7%
11765
 
8.7%
0.61743
 
8.6%
1.11298
 
6.4%
0.5995
 
4.9%
1.2924
 
4.5%
1.3775
 
3.8%
1.4557
 
2.7%
Other values (146)4798
23.6%
(Missing)461
 
2.3%
ValueCountFrequency (%)
0.14
 
< 0.1%
0.220
 
0.1%
0.386
 
0.4%
0.4336
 
1.7%
0.5995
 
4.9%
0.551
 
< 0.1%
0.61743
8.6%
0.72343
11.5%
0.82498
12.3%
0.851
 
< 0.1%
ValueCountFrequency (%)
46.61
< 0.1%
29.11
< 0.1%
21.41
< 0.1%
19.91
< 0.1%
18.81
< 0.1%
18.51
< 0.1%
17.61
< 0.1%
17.31
< 0.1%
171
< 0.1%
161
< 0.1%

Bilirubin_direct-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct97
Distinct (%)16.6%
Missing19750
Missing (%)97.1%
Infinite0
Infinite (%)0.0%
Mean2.391296928
Minimum0.1
Maximum37.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:00.208398image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.1
Q10.4
median0.9
Q32.6
95-th percentile9.425
Maximum37.5
Range37.4
Interquartile range (IQR)2.2

Descriptive statistics

Standard deviation4.170667948
Coefficient of variation (CV)1.744102917
Kurtosis22.4578301
Mean2.391296928
Median Absolute Deviation (MAD)0.7
Skewness4.136988138
Sum1401.3
Variance17.39447114
MonotonicityNot monotonic
2021-11-29T11:28:00.307868image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.259
 
0.3%
0.144
 
0.2%
0.443
 
0.2%
0.340
 
0.2%
0.530
 
0.1%
0.628
 
0.1%
0.723
 
0.1%
0.821
 
0.1%
1.118
 
0.1%
114
 
0.1%
Other values (87)266
 
1.3%
(Missing)19750
97.1%
ValueCountFrequency (%)
0.144
0.2%
0.259
0.3%
0.340
0.2%
0.443
0.2%
0.530
0.1%
0.628
0.1%
0.723
 
0.1%
0.821
 
0.1%
0.914
 
0.1%
114
 
0.1%
ValueCountFrequency (%)
37.51
< 0.1%
351
< 0.1%
301
< 0.1%
22.81
< 0.1%
22.21
< 0.1%
21.21
< 0.1%
211
< 0.1%
19.81
< 0.1%
19.21
< 0.1%
181
< 0.1%

Bilirubin_direct-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct112
Distinct (%)19.1%
Missing19750
Missing (%)97.1%
Infinite0
Infinite (%)0.0%
Mean2.905631399
Minimum0.1
Maximum37.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:00.410764image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.1
Q10.4
median1.1
Q33.3
95-th percentile11.8
Maximum37.5
Range37.4
Interquartile range (IQR)2.9

Descriptive statistics

Standard deviation4.739387861
Coefficient of variation (CV)1.631104297
Kurtosis15.48354135
Mean2.905631399
Median Absolute Deviation (MAD)0.9
Skewness3.501304236
Sum1702.7
Variance22.46179729
MonotonicityNot monotonic
2021-11-29T11:28:00.508287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.253
 
0.3%
0.143
 
0.2%
0.440
 
0.2%
0.331
 
0.2%
0.526
 
0.1%
0.626
 
0.1%
0.720
 
0.1%
0.819
 
0.1%
1.119
 
0.1%
118
 
0.1%
Other values (102)291
 
1.4%
(Missing)19750
97.1%
ValueCountFrequency (%)
0.143
0.2%
0.253
0.3%
0.331
0.2%
0.440
0.2%
0.526
0.1%
0.626
0.1%
0.720
 
0.1%
0.819
 
0.1%
0.99
 
< 0.1%
118
 
0.1%
ValueCountFrequency (%)
37.51
< 0.1%
351
< 0.1%
301
< 0.1%
29.11
< 0.1%
281
< 0.1%
26.41
< 0.1%
22.21
< 0.1%
21.61
< 0.1%
21.21
< 0.1%
211
< 0.1%

Glucose-min
Real number (ℝ≥0)

MISSING

Distinct419
Distinct (%)2.1%
Missing407
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean107.2559878
Minimum10
Maximum666
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:00.610894image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile64
Q187
median102
Q3121
95-th percentile165
Maximum666
Range656
Interquartile range (IQR)34

Descriptive statistics

Standard deviation35.1406194
Coefficient of variation (CV)0.3276331712
Kurtosis17.1122498
Mean107.2559878
Median Absolute Deviation (MAD)17
Skewness2.461324942
Sum2137504.58
Variance1234.863132
MonotonicityNot monotonic
2021-11-29T11:28:00.709643image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100370
 
1.8%
97344
 
1.7%
98343
 
1.7%
95334
 
1.6%
88334
 
1.6%
103328
 
1.6%
106323
 
1.6%
90318
 
1.6%
102318
 
1.6%
96318
 
1.6%
Other values (409)16599
81.6%
(Missing)407
 
2.0%
ValueCountFrequency (%)
101
 
< 0.1%
111
 
< 0.1%
141
 
< 0.1%
171
 
< 0.1%
181
 
< 0.1%
192
< 0.1%
212
< 0.1%
221
 
< 0.1%
242
< 0.1%
253
< 0.1%
ValueCountFrequency (%)
6661
< 0.1%
6511
< 0.1%
5631
< 0.1%
5011
< 0.1%
4721
< 0.1%
4342
< 0.1%
4201
< 0.1%
4181
< 0.1%
4152
< 0.1%
4071
< 0.1%

Glucose-max
Real number (ℝ≥0)

MISSING

Distinct676
Distinct (%)3.4%
Missing407
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean163.8167745
Minimum19
Maximum988
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:00.817225image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile93
Q1123
median149
Q3184
95-th percentile280
Maximum988
Range969
Interquartile range (IQR)61

Descriptive statistics

Standard deviation70.79349599
Coefficient of variation (CV)0.4321504692
Kurtosis21.57353284
Mean163.8167745
Median Absolute Deviation (MAD)30
Skewness3.39599843
Sum3264704.5
Variance5011.719074
MonotonicityNot monotonic
2021-11-29T11:28:00.919710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
142207
 
1.0%
145195
 
1.0%
124195
 
1.0%
129195
 
1.0%
136194
 
1.0%
144194
 
1.0%
149193
 
0.9%
131193
 
0.9%
134193
 
0.9%
127191
 
0.9%
Other values (666)17979
88.4%
(Missing)407
 
2.0%
ValueCountFrequency (%)
191
< 0.1%
311
< 0.1%
382
< 0.1%
401
< 0.1%
411
< 0.1%
421
< 0.1%
461
< 0.1%
471
< 0.1%
481
< 0.1%
512
< 0.1%
ValueCountFrequency (%)
9881
< 0.1%
9601
< 0.1%
9521
< 0.1%
9341
< 0.1%
9241
< 0.1%
9141
< 0.1%
9131
< 0.1%
9121
< 0.1%
9071
< 0.1%
8961
< 0.1%

Lactate-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct171
Distinct (%)2.2%
Missing12603
Missing (%)62.0%
Infinite0
Infinite (%)0.0%
Mean1.679900427
Minimum0.2
Maximum26.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:01.020372image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.7
Q11
median1.3
Q31.9
95-th percentile3.57
Maximum26.9
Range26.7
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation1.385789896
Coefficient of variation (CV)0.8249238309
Kurtosis55.27437723
Mean1.679900427
Median Absolute Deviation (MAD)0.4
Skewness5.854482183
Sum12990.67
Variance1.920413635
MonotonicityNot monotonic
2021-11-29T11:28:01.120270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1620
 
3.0%
0.9588
 
2.9%
1.2573
 
2.8%
1.1545
 
2.7%
1.3508
 
2.5%
0.8482
 
2.4%
1.4471
 
2.3%
1.6393
 
1.9%
1.5380
 
1.9%
1.7302
 
1.5%
Other values (161)2871
 
14.1%
(Missing)12603
62.0%
ValueCountFrequency (%)
0.21
 
< 0.1%
0.35
 
< 0.1%
0.371
 
< 0.1%
0.418
 
0.1%
0.550
 
0.2%
0.551
 
< 0.1%
0.6166
0.8%
0.7299
1.5%
0.731
 
< 0.1%
0.751
 
< 0.1%
ValueCountFrequency (%)
26.91
< 0.1%
22.41
< 0.1%
17.81
< 0.1%
17.51
< 0.1%
17.41
< 0.1%
16.751
< 0.1%
16.71
< 0.1%
16.42
< 0.1%
15.42
< 0.1%
15.31
< 0.1%

Lactate-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct248
Distinct (%)3.2%
Missing12603
Missing (%)62.0%
Infinite0
Infinite (%)0.0%
Mean2.607383939
Minimum0.3
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:01.219501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.8
Q11.3
median1.9
Q33
95-th percentile6.6
Maximum31
Range30.7
Interquartile range (IQR)1.7

Descriptive statistics

Standard deviation2.392212533
Coefficient of variation (CV)0.9174761329
Kurtosis24.48338048
Mean2.607383939
Median Absolute Deviation (MAD)0.7
Skewness4.019000215
Sum20162.9
Variance5.722680804
MonotonicityNot monotonic
2021-11-29T11:28:01.317980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.3378
 
1.9%
1.4367
 
1.8%
1.2357
 
1.8%
1350
 
1.7%
1.6348
 
1.7%
1.5329
 
1.6%
1.1302
 
1.5%
1.7292
 
1.4%
1.8288
 
1.4%
0.9270
 
1.3%
Other values (238)4452
 
21.9%
(Missing)12603
62.0%
ValueCountFrequency (%)
0.32
 
< 0.1%
0.371
 
< 0.1%
0.45
 
< 0.1%
0.518
 
0.1%
0.551
 
< 0.1%
0.656
 
0.3%
0.7114
0.6%
0.731
 
< 0.1%
0.8210
1.0%
0.9270
1.3%
ValueCountFrequency (%)
311
< 0.1%
28.91
< 0.1%
28.81
< 0.1%
271
< 0.1%
25.91
< 0.1%
24.61
< 0.1%
24.51
< 0.1%
241
< 0.1%
23.51
< 0.1%
23.31
< 0.1%

Magnesium-min
Real number (ℝ≥0)

MISSING

Distinct47
Distinct (%)0.2%
Missing1388
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean1.864042643
Minimum0.2
Maximum8.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:01.421993image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile1.4
Q11.7
median1.8
Q32
95-th percentile2.4
Maximum8.2
Range8
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.3432759491
Coefficient of variation (CV)0.1841567039
Kurtosis12.96717616
Mean1.864042643
Median Absolute Deviation (MAD)0.2
Skewness1.286745587
Sum35319.88
Variance0.1178383772
MonotonicityNot monotonic
2021-11-29T11:28:01.602881image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
1.82691
13.2%
1.92565
12.6%
1.72362
11.6%
22041
10.0%
1.61757
8.6%
2.11539
7.6%
1.51189
5.8%
2.21075
 
5.3%
1.4728
 
3.6%
2.3718
 
3.5%
Other values (37)2283
11.2%
(Missing)1388
6.8%
ValueCountFrequency (%)
0.21
 
< 0.1%
0.75
 
< 0.1%
0.87
 
< 0.1%
0.925
 
0.1%
178
 
0.4%
1.1129
 
0.6%
1.141
 
< 0.1%
1.2249
 
1.2%
1.3430
2.1%
1.4728
3.6%
ValueCountFrequency (%)
8.21
 
< 0.1%
6.52
 
< 0.1%
6.21
 
< 0.1%
4.61
 
< 0.1%
4.51
 
< 0.1%
4.21
 
< 0.1%
4.12
 
< 0.1%
43
< 0.1%
3.81
 
< 0.1%
3.75
< 0.1%

Magnesium-max
Real number (ℝ≥0)

MISSING

Distinct63
Distinct (%)0.3%
Missing1388
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean2.180462318
Minimum0.8
Maximum9.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:01.707226image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.8
5-th percentile1.6
Q11.9
median2.1
Q32.4
95-th percentile2.9
Maximum9.7
Range8.9
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.4214289648
Coefficient of variation (CV)0.1932750506
Kurtosis31.062933
Mean2.180462318
Median Absolute Deviation (MAD)0.2
Skewness2.896517979
Sum41315.4
Variance0.1776023724
MonotonicityNot monotonic
2021-11-29T11:28:01.800403image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.12458
12.1%
22321
11.4%
2.22220
10.9%
1.91857
9.1%
2.31809
8.9%
2.41408
6.9%
1.81357
6.7%
2.51009
 
5.0%
1.7895
 
4.4%
2.6735
 
3.6%
Other values (53)2879
14.2%
(Missing)1388
6.8%
ValueCountFrequency (%)
0.81
 
< 0.1%
0.92
 
< 0.1%
18
 
< 0.1%
1.112
 
0.1%
1.228
 
0.1%
1.373
 
0.4%
1.4122
 
0.6%
1.5234
 
1.2%
1.6535
2.6%
1.7895
4.4%
ValueCountFrequency (%)
9.71
 
< 0.1%
9.61
 
< 0.1%
8.92
< 0.1%
8.31
 
< 0.1%
8.21
 
< 0.1%
7.61
 
< 0.1%
7.51
 
< 0.1%
6.51
 
< 0.1%
6.41
 
< 0.1%
6.33
< 0.1%

Phosphate-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct114
Distinct (%)0.7%
Missing3650
Missing (%)17.9%
Infinite0
Infinite (%)0.0%
Mean3.207590195
Minimum0.2
Maximum13.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:01.895718image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile1.6
Q12.4
median3.1
Q33.8
95-th percentile5.3
Maximum13.5
Range13.3
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.19385278
Coefficient of variation (CV)0.3721961681
Kurtosis4.851664704
Mean3.207590195
Median Absolute Deviation (MAD)0.7
Skewness1.38697156
Sum53521.85
Variance1.425284459
MonotonicityNot monotonic
2021-11-29T11:28:02.004969image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.9714
 
3.5%
3.1712
 
3.5%
2.7708
 
3.5%
3.2688
 
3.4%
2.8678
 
3.3%
2.6655
 
3.2%
3.3623
 
3.1%
3619
 
3.0%
2.5605
 
3.0%
3.4579
 
2.8%
Other values (104)10105
49.7%
(Missing)3650
 
17.9%
ValueCountFrequency (%)
0.21
 
< 0.1%
0.35
 
< 0.1%
0.43
 
< 0.1%
0.511
 
0.1%
0.613
 
0.1%
0.724
 
0.1%
0.827
 
0.1%
0.923
 
0.1%
151
0.3%
1.175
0.4%
ValueCountFrequency (%)
13.51
 
< 0.1%
12.91
 
< 0.1%
12.41
 
< 0.1%
12.31
 
< 0.1%
12.22
< 0.1%
12.11
 
< 0.1%
11.21
 
< 0.1%
11.11
 
< 0.1%
113
< 0.1%
10.53
< 0.1%

Phosphate-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct138
Distinct (%)0.8%
Missing3650
Missing (%)17.9%
Infinite0
Infinite (%)0.0%
Mean3.925970874
Minimum0.5
Maximum18.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:02.110460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile2.3
Q13.1
median3.7
Q34.4
95-th percentile6.4
Maximum18.8
Range18.3
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation1.376467273
Coefficient of variation (CV)0.3506055743
Kurtosis8.827872226
Mean3.925970874
Median Absolute Deviation (MAD)0.7
Skewness2.076309712
Sum65508.75
Variance1.894662153
MonotonicityNot monotonic
2021-11-29T11:28:02.208622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.4731
 
3.6%
3.6712
 
3.5%
3.7706
 
3.5%
3.2702
 
3.5%
3.5700
 
3.4%
3.3687
 
3.4%
3.1652
 
3.2%
3.8647
 
3.2%
3.9640
 
3.1%
4.1572
 
2.8%
Other values (128)9937
48.9%
(Missing)3650
 
17.9%
ValueCountFrequency (%)
0.51
 
< 0.1%
0.71
 
< 0.1%
0.81
 
< 0.1%
0.92
 
< 0.1%
15
 
< 0.1%
1.16
 
< 0.1%
1.216
0.1%
1.315
0.1%
1.423
0.1%
1.525
0.1%
ValueCountFrequency (%)
18.81
< 0.1%
17.61
< 0.1%
16.91
< 0.1%
16.51
< 0.1%
16.41
< 0.1%
15.61
< 0.1%
14.51
< 0.1%
14.21
< 0.1%
14.11
< 0.1%
141
< 0.1%

Potassium-min
Real number (ℝ≥0)

MISSING

Distinct71
Distinct (%)0.4%
Missing433
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean3.815108275
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:02.312945image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13.5
median3.8
Q34.1
95-th percentile4.7
Maximum9
Range8
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.516029457
Coefficient of variation (CV)0.1352594526
Kurtosis1.755362517
Mean3.815108275
Median Absolute Deviation (MAD)0.3
Skewness0.4984364654
Sum75932.1
Variance0.2662864004
MonotonicityNot monotonic
2021-11-29T11:28:02.412621image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.81780
 
8.8%
3.71743
 
8.6%
3.61665
 
8.2%
3.91581
 
7.8%
3.51427
 
7.0%
41376
 
6.8%
3.41258
 
6.2%
4.11204
 
5.9%
4.21019
 
5.0%
3.3966
 
4.8%
Other values (61)5884
28.9%
ValueCountFrequency (%)
11
 
< 0.1%
1.51
 
< 0.1%
1.61
 
< 0.1%
1.82
 
< 0.1%
1.95
 
< 0.1%
24
 
< 0.1%
2.110
 
< 0.1%
2.26
 
< 0.1%
2.314
0.1%
2.426
0.1%
ValueCountFrequency (%)
91
 
< 0.1%
7.11
 
< 0.1%
6.91
 
< 0.1%
6.71
 
< 0.1%
6.53
< 0.1%
6.42
 
< 0.1%
6.32
 
< 0.1%
6.26
< 0.1%
6.12
 
< 0.1%
66
< 0.1%

Potassium-max
Real number (ℝ≥0)

MISSING

Distinct102
Distinct (%)0.5%
Missing433
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean4.480864191
Minimum2.2
Maximum27.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:02.515332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile3.6
Q14
median4.4
Q34.8
95-th percentile5.7
Maximum27.5
Range25.3
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.719283605
Coefficient of variation (CV)0.1605234112
Kurtosis59.32436812
Mean4.480864191
Median Absolute Deviation (MAD)0.4
Skewness3.297248628
Sum89182.64
Variance0.5173689044
MonotonicityNot monotonic
2021-11-29T11:28:02.615541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.21529
 
7.5%
4.31525
 
7.5%
4.41424
 
7.0%
4.11417
 
7.0%
41336
 
6.6%
4.51336
 
6.6%
4.61187
 
5.8%
3.91078
 
5.3%
4.71024
 
5.0%
4.8872
 
4.3%
Other values (92)7175
35.3%
ValueCountFrequency (%)
2.21
 
< 0.1%
2.51
 
< 0.1%
2.72
 
< 0.1%
2.87
 
< 0.1%
2.93
 
< 0.1%
332
 
0.2%
3.149
 
0.2%
3.280
0.4%
3.3129
0.6%
3.351
 
< 0.1%
ValueCountFrequency (%)
27.51
 
< 0.1%
131
 
< 0.1%
103
< 0.1%
9.93
< 0.1%
9.83
< 0.1%
9.73
< 0.1%
9.52
< 0.1%
9.42
< 0.1%
9.31
 
< 0.1%
9.24
< 0.1%

Bilirubin_total-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct206
Distinct (%)3.6%
Missing14566
Missing (%)71.6%
Infinite0
Infinite (%)0.0%
Mean1.586646447
Minimum0.1
Maximum45.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:02.714084image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.2
Q10.4
median0.7
Q31.2
95-th percentile5.6
Maximum45.9
Range45.8
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation3.545279592
Coefficient of variation (CV)2.234448385
Kurtosis51.58048869
Mean1.586646447
Median Absolute Deviation (MAD)0.3
Skewness6.412716124
Sum9154.95
Variance12.56900739
MonotonicityNot monotonic
2021-11-29T11:28:02.813980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3631
 
3.1%
0.4618
 
3.0%
0.5596
 
2.9%
0.6488
 
2.4%
0.7417
 
2.1%
0.2394
 
1.9%
0.8315
 
1.5%
0.9273
 
1.3%
1199
 
1.0%
1.1172
 
0.8%
Other values (196)1667
 
8.2%
(Missing)14566
71.6%
ValueCountFrequency (%)
0.188
 
0.4%
0.2394
1.9%
0.3631
3.1%
0.4618
3.0%
0.451
 
< 0.1%
0.5596
2.9%
0.6488
2.4%
0.7417
2.1%
0.8315
1.5%
0.9273
1.3%
ValueCountFrequency (%)
45.91
< 0.1%
44.91
< 0.1%
44.11
< 0.1%
43.51
< 0.1%
43.21
< 0.1%
40.61
< 0.1%
40.12
< 0.1%
38.71
< 0.1%
36.31
< 0.1%
34.71
< 0.1%

Bilirubin_total-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct240
Distinct (%)4.2%
Missing14566
Missing (%)71.6%
Infinite0
Infinite (%)0.0%
Mean1.9555026
Minimum0.1
Maximum46.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:02.915087image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.2
Q10.4
median0.7
Q31.5
95-th percentile7.8
Maximum46.6
Range46.5
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation4.244483696
Coefficient of variation (CV)2.170533395
Kurtosis39.29864828
Mean1.9555026
Median Absolute Deviation (MAD)0.4
Skewness5.637871326
Sum11283.25
Variance18.01564184
MonotonicityNot monotonic
2021-11-29T11:28:03.014712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3549
 
2.7%
0.5546
 
2.7%
0.4538
 
2.6%
0.6457
 
2.2%
0.7420
 
2.1%
0.8348
 
1.7%
0.2325
 
1.6%
0.9274
 
1.3%
1218
 
1.1%
1.1182
 
0.9%
Other values (230)1913
 
9.4%
(Missing)14566
71.6%
ValueCountFrequency (%)
0.159
 
0.3%
0.2325
1.6%
0.3549
2.7%
0.4538
2.6%
0.5546
2.7%
0.6457
2.2%
0.7420
2.1%
0.8348
1.7%
0.9274
1.3%
1218
 
1.1%
ValueCountFrequency (%)
46.61
< 0.1%
46.51
< 0.1%
45.91
< 0.1%
44.61
< 0.1%
44.31
< 0.1%
44.11
< 0.1%
43.71
< 0.1%
43.21
< 0.1%
42.41
< 0.1%
40.91
< 0.1%

TroponinI-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct182
Distinct (%)37.2%
Missing19847
Missing (%)97.6%
Infinite0
Infinite (%)0.0%
Mean7.40204499
Minimum0.3
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:03.197841image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.3
Q10.7
median2.4
Q39.9
95-th percentile32.12
Maximum48
Range47.7
Interquartile range (IQR)9.2

Descriptive statistics

Standard deviation10.40468427
Coefficient of variation (CV)1.405649964
Kurtosis3.102736102
Mean7.40204499
Median Absolute Deviation (MAD)2
Skewness1.917343008
Sum3619.6
Variance108.2574548
MonotonicityNot monotonic
2021-11-29T11:28:03.301206image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.344
 
0.2%
0.430
 
0.1%
0.525
 
0.1%
0.823
 
0.1%
0.621
 
0.1%
0.718
 
0.1%
115
 
0.1%
0.911
 
0.1%
1.27
 
< 0.1%
10.77
 
< 0.1%
Other values (172)288
 
1.4%
(Missing)19847
97.6%
ValueCountFrequency (%)
0.344
0.2%
0.430
0.1%
0.525
0.1%
0.621
0.1%
0.718
0.1%
0.823
0.1%
0.911
 
0.1%
115
 
0.1%
1.16
 
< 0.1%
1.27
 
< 0.1%
ValueCountFrequency (%)
481
< 0.1%
46.51
< 0.1%
452
< 0.1%
44.81
< 0.1%
44.21
< 0.1%
43.51
< 0.1%
42.91
< 0.1%
41.51
< 0.1%
411
< 0.1%
39.91
< 0.1%

TroponinI-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct214
Distinct (%)43.8%
Missing19847
Missing (%)97.6%
Infinite0
Infinite (%)0.0%
Mean10.43271984
Minimum0.3
Maximum49.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:03.401216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.4
Q10.9
median4.2
Q315.4
95-th percentile41.3
Maximum49.3
Range49
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation12.94786966
Coefficient of variation (CV)1.24108285
Kurtosis1.077420411
Mean10.43271984
Median Absolute Deviation (MAD)3.7
Skewness1.445003395
Sum5101.6
Variance167.6473289
MonotonicityNot monotonic
2021-11-29T11:28:03.505671image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.522
 
0.1%
0.322
 
0.1%
0.821
 
0.1%
0.421
 
0.1%
0.617
 
0.1%
0.715
 
0.1%
0.911
 
0.1%
111
 
0.1%
1.18
 
< 0.1%
1.28
 
< 0.1%
Other values (204)333
 
1.6%
(Missing)19847
97.6%
ValueCountFrequency (%)
0.322
0.1%
0.421
0.1%
0.522
0.1%
0.617
0.1%
0.715
0.1%
0.821
0.1%
0.911
0.1%
111
0.1%
1.18
 
< 0.1%
1.28
 
< 0.1%
ValueCountFrequency (%)
49.31
< 0.1%
491
< 0.1%
48.71
< 0.1%
48.52
< 0.1%
482
< 0.1%
47.11
< 0.1%
46.51
< 0.1%
461
< 0.1%
45.21
< 0.1%
45.11
< 0.1%

Hct-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct485
Distinct (%)2.4%
Missing364
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean29.55105848
Minimum5.5
Maximum66.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:03.609181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5.5
5-th percentile21.8
Q125.7
median29
Q333
95-th percentile39.1
Maximum66.2
Range60.7
Interquartile range (IQR)7.3

Descriptive statistics

Standard deviation5.415361492
Coefficient of variation (CV)0.1832544
Kurtosis0.4366050879
Mean29.55105848
Median Absolute Deviation (MAD)3.6
Skewness0.4137097912
Sum590193.74
Variance29.32614009
MonotonicityNot monotonic
2021-11-29T11:28:03.704971image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26285
 
1.4%
28228
 
1.1%
27226
 
1.1%
25219
 
1.1%
29199
 
1.0%
30199
 
1.0%
24191
 
0.9%
23190
 
0.9%
26.5161
 
0.8%
27.8161
 
0.8%
Other values (475)17913
88.1%
(Missing)364
 
1.8%
ValueCountFrequency (%)
5.51
< 0.1%
71
< 0.1%
8.81
< 0.1%
9.41
< 0.1%
9.71
< 0.1%
10.31
< 0.1%
111
< 0.1%
11.51
< 0.1%
12.11
< 0.1%
12.21
< 0.1%
ValueCountFrequency (%)
66.21
< 0.1%
61.71
< 0.1%
60.32
< 0.1%
56.11
< 0.1%
55.31
< 0.1%
54.81
< 0.1%
54.11
< 0.1%
541
< 0.1%
53.82
< 0.1%
531
< 0.1%

Hct-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct407
Distinct (%)2.0%
Missing364
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean33.67926747
Minimum11
Maximum71.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:03.806239image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile26.8
Q130.4
median33.2
Q336.5
95-th percentile42
Maximum71.7
Range60.7
Interquartile range (IQR)6.1

Descriptive statistics

Standard deviation4.711327099
Coefficient of variation (CV)0.1398880514
Kurtosis1.049059462
Mean33.67926747
Median Absolute Deviation (MAD)3
Skewness0.5834176548
Sum672642.33
Variance22.19660303
MonotonicityNot monotonic
2021-11-29T11:28:03.901394image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32370
 
1.8%
34315
 
1.5%
35301
 
1.5%
33300
 
1.5%
31269
 
1.3%
36259
 
1.3%
30243
 
1.2%
37229
 
1.1%
38224
 
1.1%
29206
 
1.0%
Other values (397)17256
84.9%
(Missing)364
 
1.8%
ValueCountFrequency (%)
111
< 0.1%
12.51
< 0.1%
15.81
< 0.1%
16.81
< 0.1%
18.41
< 0.1%
18.91
< 0.1%
19.11
< 0.1%
19.52
< 0.1%
19.61
< 0.1%
19.81
< 0.1%
ValueCountFrequency (%)
71.71
< 0.1%
64.61
< 0.1%
61.81
< 0.1%
61.71
< 0.1%
611
< 0.1%
60.51
< 0.1%
58.81
< 0.1%
581
< 0.1%
56.41
< 0.1%
56.32
< 0.1%

Hgb-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct205
Distinct (%)1.0%
Missing507
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean10.16811286
Minimum2.2
Maximum20.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:04.002914image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile7.5
Q18.9
median10
Q311.3
95-th percentile13.5
Maximum20.3
Range18.1
Interquartile range (IQR)2.4

Descriptive statistics

Standard deviation1.844816211
Coefficient of variation (CV)0.1814315238
Kurtosis0.2644858416
Mean10.16811286
Median Absolute Deviation (MAD)1.2
Skewness0.3964761228
Sum201623.51
Variance3.403346852
MonotonicityNot monotonic
2021-11-29T11:28:04.102668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.8481
 
2.4%
9.4469
 
2.3%
9.7464
 
2.3%
9.2460
 
2.3%
9.5450
 
2.2%
10440
 
2.2%
9.6426
 
2.1%
9422
 
2.1%
9.3421
 
2.1%
9.9421
 
2.1%
Other values (195)15375
75.6%
(Missing)507
 
2.5%
ValueCountFrequency (%)
2.21
 
< 0.1%
3.11
 
< 0.1%
3.22
< 0.1%
41
 
< 0.1%
4.051
 
< 0.1%
4.12
< 0.1%
4.22
< 0.1%
4.33
< 0.1%
4.41
 
< 0.1%
4.52
< 0.1%
ValueCountFrequency (%)
20.31
 
< 0.1%
19.32
< 0.1%
19.11
 
< 0.1%
18.61
 
< 0.1%
18.41
 
< 0.1%
182
< 0.1%
17.41
 
< 0.1%
17.13
< 0.1%
171
 
< 0.1%
16.92
< 0.1%

Hgb-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct184
Distinct (%)0.9%
Missing507
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean11.34229311
Minimum3.5
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:04.209677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3.5
5-th percentile8.8
Q110.2
median11.2
Q312.4
95-th percentile14.4
Maximum32
Range28.5
Interquartile range (IQR)2.2

Descriptive statistics

Standard deviation1.700859441
Coefficient of variation (CV)0.1499572816
Kurtosis1.527280706
Mean11.34229311
Median Absolute Deviation (MAD)1.1
Skewness0.5419012209
Sum224906.33
Variance2.892922838
MonotonicityNot monotonic
2021-11-29T11:28:04.303336image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11522
 
2.6%
10.7505
 
2.5%
11.1504
 
2.5%
10.9496
 
2.4%
11.3495
 
2.4%
10.5493
 
2.4%
11.2484
 
2.4%
10.6482
 
2.4%
10.8465
 
2.3%
11.4462
 
2.3%
Other values (174)14921
73.4%
(Missing)507
 
2.5%
ValueCountFrequency (%)
3.51
< 0.1%
4.41
< 0.1%
5.41
< 0.1%
5.61
< 0.1%
5.71
< 0.1%
61
< 0.1%
6.21
< 0.1%
6.32
< 0.1%
6.42
< 0.1%
6.52
< 0.1%
ValueCountFrequency (%)
321
< 0.1%
22.11
< 0.1%
20.31
< 0.1%
19.61
< 0.1%
19.51
< 0.1%
19.41
< 0.1%
19.31
< 0.1%
18.81
< 0.1%
18.71
< 0.1%
18.61
< 0.1%

PTT-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct688
Distinct (%)4.3%
Missing4496
Missing (%)22.1%
Infinite0
Infinite (%)0.0%
Mean31.89517109
Minimum12.5
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:04.402678image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum12.5
5-th percentile22.3
Q125.9
median29.1
Q333.9
95-th percentile50.7
Maximum150
Range137.5
Interquartile range (IQR)8

Descriptive statistics

Standard deviation11.61275924
Coefficient of variation (CV)0.3640914548
Kurtosis32.60193918
Mean31.89517109
Median Absolute Deviation (MAD)3.7
Skewness4.498845459
Sum505219.51
Variance134.8561772
MonotonicityNot monotonic
2021-11-29T11:28:04.498882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.7155
 
0.8%
27.6145
 
0.7%
28.1140
 
0.7%
27136
 
0.7%
28.5135
 
0.7%
26.7133
 
0.7%
28.6133
 
0.7%
26.2133
 
0.7%
28.7132
 
0.6%
26.6131
 
0.6%
Other values (678)14467
71.1%
(Missing)4496
 
22.1%
ValueCountFrequency (%)
12.51
 
< 0.1%
16.61
 
< 0.1%
17.13
< 0.1%
17.21
 
< 0.1%
17.31
 
< 0.1%
17.41
 
< 0.1%
17.51
 
< 0.1%
17.92
< 0.1%
18.13
< 0.1%
18.23
< 0.1%
ValueCountFrequency (%)
15034
0.2%
145.91
 
< 0.1%
143.71
 
< 0.1%
142.11
 
< 0.1%
1391
 
< 0.1%
137.81
 
< 0.1%
135.31
 
< 0.1%
1311
 
< 0.1%
127.91
 
< 0.1%
127.21
 
< 0.1%

PTT-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1136
Distinct (%)7.2%
Missing4496
Missing (%)22.1%
Infinite0
Infinite (%)0.0%
Mean42.74270896
Minimum17.1
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:04.601837image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum17.1
5-th percentile23.4
Q127.7
median32.4
Q343
95-th percentile114.905
Maximum150
Range132.9
Interquartile range (IQR)15.3

Descriptive statistics

Standard deviation28.25780232
Coefficient of variation (CV)0.6611139772
Kurtosis6.122138596
Mean42.74270896
Median Absolute Deviation (MAD)6
Skewness2.545713447
Sum677044.51
Variance798.5033919
MonotonicityNot monotonic
2021-11-29T11:28:04.788126image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150511
 
2.5%
27.7112
 
0.6%
27.6106
 
0.5%
28.1105
 
0.5%
29.3104
 
0.5%
28.6103
 
0.5%
28.2101
 
0.5%
29.2100
 
0.5%
28.8100
 
0.5%
2799
 
0.5%
Other values (1126)14399
70.8%
(Missing)4496
 
22.1%
ValueCountFrequency (%)
17.11
 
< 0.1%
17.21
 
< 0.1%
17.31
 
< 0.1%
18.11
 
< 0.1%
18.21
 
< 0.1%
18.42
< 0.1%
18.53
< 0.1%
18.61
 
< 0.1%
18.74
< 0.1%
18.83
< 0.1%
ValueCountFrequency (%)
150511
2.5%
149.91
 
< 0.1%
149.81
 
< 0.1%
148.91
 
< 0.1%
148.82
 
< 0.1%
148.71
 
< 0.1%
148.31
 
< 0.1%
148.21
 
< 0.1%
1481
 
< 0.1%
147.71
 
< 0.1%

WBC-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct429
Distinct (%)2.2%
Missing625
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean10.40438385
Minimum0.1
Maximum201.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:04.890327image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile4.3
Q17.2
median9.6
Q312.5
95-th percentile18.5
Maximum201.6
Range201.5
Interquartile range (IQR)5.3

Descriptive statistics

Standard deviation5.88137598
Coefficient of variation (CV)0.5652786428
Kurtosis174.8237677
Mean10.40438385
Median Absolute Deviation (MAD)2.6
Skewness8.145523781
Sum205080.81
Variance34.59058341
MonotonicityNot monotonic
2021-11-29T11:28:04.992706image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.5229
 
1.1%
9.4225
 
1.1%
8219
 
1.1%
9.3217
 
1.1%
7.2216
 
1.1%
8.9215
 
1.1%
7.7214
 
1.1%
8.8213
 
1.0%
8.4213
 
1.0%
7.4213
 
1.0%
Other values (419)17537
86.2%
(Missing)625
 
3.1%
ValueCountFrequency (%)
0.114
0.1%
0.210
< 0.1%
0.36
< 0.1%
0.46
< 0.1%
0.52
 
< 0.1%
0.64
 
< 0.1%
0.74
 
< 0.1%
0.81
 
< 0.1%
0.95
 
< 0.1%
18
< 0.1%
ValueCountFrequency (%)
201.61
< 0.1%
180.41
< 0.1%
168.61
< 0.1%
128.31
< 0.1%
126.21
< 0.1%
124.41
< 0.1%
120.51
< 0.1%
119.91
< 0.1%
116.51
< 0.1%
97.11
< 0.1%

WBC-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct532
Distinct (%)2.7%
Missing625
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean13.24228705
Minimum0.1
Maximum422.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:05.102029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile5.5
Q19
median12.1
Q315.9
95-th percentile24.2
Maximum422.9
Range422.8
Interquartile range (IQR)6.9

Descriptive statistics

Standard deviation7.949554985
Coefficient of variation (CV)0.6003158636
Kurtosis445.6163799
Mean13.24228705
Median Absolute Deviation (MAD)3.4
Skewness12.18112024
Sum261018.72
Variance63.19542446
MonotonicityNot monotonic
2021-11-29T11:28:05.197900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.6195
 
1.0%
11.5186
 
0.9%
10.7186
 
0.9%
9.5180
 
0.9%
9.8180
 
0.9%
11.2176
 
0.9%
10.2173
 
0.9%
10.3173
 
0.9%
11.8172
 
0.8%
10.4168
 
0.8%
Other values (522)17922
88.1%
(Missing)625
 
3.1%
ValueCountFrequency (%)
0.16
< 0.1%
0.210
< 0.1%
0.36
< 0.1%
0.42
 
< 0.1%
0.52
 
< 0.1%
0.63
 
< 0.1%
0.74
 
< 0.1%
0.83
 
< 0.1%
0.91
 
< 0.1%
11
 
< 0.1%
ValueCountFrequency (%)
422.91
< 0.1%
224.91
< 0.1%
222.81
< 0.1%
170.31
< 0.1%
168.61
< 0.1%
137.81
< 0.1%
128.71
< 0.1%
126.21
< 0.1%
125.71
< 0.1%
123.11
< 0.1%

Fibrinogen-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct644
Distinct (%)25.1%
Missing17769
Missing (%)87.4%
Infinite0
Infinite (%)0.0%
Mean292.9410206
Minimum34
Maximum1383
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:05.295599image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile105.3
Q1176
median242
Q3367
95-th percentile648
Maximum1383
Range1349
Interquartile range (IQR)191

Descriptive statistics

Standard deviation169.5769129
Coefficient of variation (CV)0.5788773199
Kurtosis2.436807156
Mean292.9410206
Median Absolute Deviation (MAD)85
Skewness1.427978388
Sum751979.6
Variance28756.3294
MonotonicityNot monotonic
2021-11-29T11:28:05.399270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21719
 
0.1%
21418
 
0.1%
15117
 
0.1%
18517
 
0.1%
20215
 
0.1%
18315
 
0.1%
21014
 
0.1%
20314
 
0.1%
24214
 
0.1%
18014
 
0.1%
Other values (634)2410
 
11.9%
(Missing)17769
87.4%
ValueCountFrequency (%)
341
 
< 0.1%
351
 
< 0.1%
501
 
< 0.1%
521
 
< 0.1%
52.51
 
< 0.1%
561
 
< 0.1%
581
 
< 0.1%
595
< 0.1%
601
 
< 0.1%
611
 
< 0.1%
ValueCountFrequency (%)
13831
< 0.1%
12461
< 0.1%
11611
< 0.1%
10301
< 0.1%
9761
< 0.1%
9601
< 0.1%
9561
< 0.1%
9461
< 0.1%
9101
< 0.1%
9041
< 0.1%

Fibrinogen-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct650
Distinct (%)25.3%
Missing17769
Missing (%)87.4%
Infinite0
Infinite (%)0.0%
Mean330.9836774
Minimum52.5
Maximum1760
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:05.503289image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum52.5
5-th percentile133.3
Q1203
median286
Q3416
95-th percentile676
Maximum1760
Range1707.5
Interquartile range (IQR)213

Descriptive statistics

Standard deviation175.8937644
Coefficient of variation (CV)0.5314273071
Kurtosis3.366347057
Mean330.9836774
Median Absolute Deviation (MAD)96
Skewness1.434675366
Sum849635.1
Variance30938.61635
MonotonicityNot monotonic
2021-11-29T11:28:05.601055image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21417
 
0.1%
18515
 
0.1%
21615
 
0.1%
21014
 
0.1%
23314
 
0.1%
18313
 
0.1%
28013
 
0.1%
21712
 
0.1%
20312
 
0.1%
21512
 
0.1%
Other values (640)2430
 
11.9%
(Missing)17769
87.4%
ValueCountFrequency (%)
52.51
< 0.1%
581
< 0.1%
631
< 0.1%
651
< 0.1%
762
< 0.1%
811
< 0.1%
821
< 0.1%
852
< 0.1%
871
< 0.1%
881
< 0.1%
ValueCountFrequency (%)
17601
< 0.1%
13831
< 0.1%
12461
< 0.1%
11611
< 0.1%
10761
< 0.1%
10302
< 0.1%
9941
< 0.1%
9791
< 0.1%
9761
< 0.1%
9601
< 0.1%

Platelets-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct704
Distinct (%)3.6%
Missing585
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean195.8909675
Minimum5
Maximum1592
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:05.706313image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile68
Q1129
median178
Q3241
95-th percentile379
Maximum1592
Range1587
Interquartile range (IQR)112

Descriptive statistics

Standard deviation103.0525545
Coefficient of variation (CV)0.5260709862
Kurtosis9.396094818
Mean195.8909675
Median Absolute Deviation (MAD)55
Skewness1.94562446
Sum3869042.5
Variance10619.82898
MonotonicityNot monotonic
2021-11-29T11:28:05.805824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160133
 
0.7%
195122
 
0.6%
172119
 
0.6%
179119
 
0.6%
158112
 
0.6%
170112
 
0.6%
156110
 
0.5%
125110
 
0.5%
188109
 
0.5%
157109
 
0.5%
Other values (694)18596
91.4%
(Missing)585
 
2.9%
ValueCountFrequency (%)
55
< 0.1%
62
 
< 0.1%
75
< 0.1%
81
 
< 0.1%
93
< 0.1%
103
< 0.1%
113
< 0.1%
127
< 0.1%
135
< 0.1%
144
< 0.1%
ValueCountFrequency (%)
15921
< 0.1%
14211
< 0.1%
13431
< 0.1%
12621
< 0.1%
11421
< 0.1%
10241
< 0.1%
10071
< 0.1%
9921
< 0.1%
9841
< 0.1%
9611
< 0.1%

Platelets-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct753
Distinct (%)3.8%
Missing585
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean229.3742595
Minimum10
Maximum1783
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:05.914232image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile98
Q1158
median208
Q3275
95-th percentile430.5
Maximum1783
Range1773
Interquartile range (IQR)117

Descriptive statistics

Standard deviation111.6872719
Coefficient of variation (CV)0.4869215584
Kurtosis11.07361937
Mean229.3742595
Median Absolute Deviation (MAD)57
Skewness2.14067279
Sum4530371
Variance12474.04671
MonotonicityNot monotonic
2021-11-29T11:28:06.013445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
167113
 
0.6%
186113
 
0.6%
172112
 
0.6%
197112
 
0.6%
155110
 
0.5%
192109
 
0.5%
198108
 
0.5%
187108
 
0.5%
188108
 
0.5%
207107
 
0.5%
Other values (743)18651
91.7%
(Missing)585
 
2.9%
ValueCountFrequency (%)
101
 
< 0.1%
131
 
< 0.1%
142
< 0.1%
162
< 0.1%
171
 
< 0.1%
183
< 0.1%
192
< 0.1%
201
 
< 0.1%
212
< 0.1%
223
< 0.1%
ValueCountFrequency (%)
17831
< 0.1%
16671
< 0.1%
13431
< 0.1%
13391
< 0.1%
12742
< 0.1%
12531
< 0.1%
12011
< 0.1%
11971
< 0.1%
11292
< 0.1%
11111
< 0.1%

Age-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5971
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.6216129
Minimum18.11
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:06.121001image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum18.11
5-th percentile30.8475
Q152.29
median64.67
Q375.66
95-th percentile84.95
Maximum89
Range70.89
Interquartile range (IQR)23.37

Descriptive statistics

Standard deviation16.23615352
Coefficient of variation (CV)0.2592739594
Kurtosis-0.2520549698
Mean62.6216129
Median Absolute Deviation (MAD)11.61
Skewness-0.5902903968
Sum1273473.12
Variance263.6126812
MonotonicityNot monotonic
2021-11-29T11:28:06.220972image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
65.8213
 
0.1%
69.6812
 
0.1%
61.0812
 
0.1%
68.1712
 
0.1%
65.4712
 
0.1%
71.3712
 
0.1%
68.3711
 
0.1%
69.5811
 
0.1%
78.4211
 
0.1%
60.8811
 
0.1%
Other values (5961)20219
99.4%
ValueCountFrequency (%)
18.113
< 0.1%
18.131
 
< 0.1%
18.142
< 0.1%
18.151
 
< 0.1%
18.181
 
< 0.1%
18.241
 
< 0.1%
18.321
 
< 0.1%
18.341
 
< 0.1%
18.352
< 0.1%
18.361
 
< 0.1%
ValueCountFrequency (%)
891
 
< 0.1%
88.991
 
< 0.1%
88.982
 
< 0.1%
88.974
< 0.1%
88.961
 
< 0.1%
88.954
< 0.1%
88.942
 
< 0.1%
88.931
 
< 0.1%
88.925
< 0.1%
88.94
< 0.1%

Age-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct5971
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.6216129
Minimum18.11
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:06.414692image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum18.11
5-th percentile30.8475
Q152.29
median64.67
Q375.66
95-th percentile84.95
Maximum89
Range70.89
Interquartile range (IQR)23.37

Descriptive statistics

Standard deviation16.23615352
Coefficient of variation (CV)0.2592739594
Kurtosis-0.2520549698
Mean62.6216129
Median Absolute Deviation (MAD)11.61
Skewness-0.5902903968
Sum1273473.12
Variance263.6126812
MonotonicityNot monotonic
2021-11-29T11:28:06.515801image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
65.8213
 
0.1%
69.6812
 
0.1%
61.0812
 
0.1%
68.1712
 
0.1%
65.4712
 
0.1%
71.3712
 
0.1%
68.3711
 
0.1%
69.5811
 
0.1%
78.4211
 
0.1%
60.8811
 
0.1%
Other values (5961)20219
99.4%
ValueCountFrequency (%)
18.113
< 0.1%
18.131
 
< 0.1%
18.142
< 0.1%
18.151
 
< 0.1%
18.181
 
< 0.1%
18.241
 
< 0.1%
18.321
 
< 0.1%
18.341
 
< 0.1%
18.352
< 0.1%
18.361
 
< 0.1%
ValueCountFrequency (%)
891
 
< 0.1%
88.991
 
< 0.1%
88.982
 
< 0.1%
88.974
< 0.1%
88.961
 
< 0.1%
88.954
< 0.1%
88.942
 
< 0.1%
88.931
 
< 0.1%
88.925
< 0.1%
88.94
< 0.1%

Gender-min
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size159.0 KiB
1
11834 
0
8502 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20336
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Length

2021-11-29T11:28:06.615034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:28:06.660264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Most occurring characters

ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Most occurring scripts

ValueCountFrequency (%)
Common20336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII20336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Gender-max
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size159.0 KiB
1
11834 
0
8502 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20336
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Length

2021-11-29T11:28:07.129518image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:28:07.183563image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Most occurring characters

ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Most occurring scripts

ValueCountFrequency (%)
Common20336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII20336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111834
58.2%
08502
41.8%

Unit1-min
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing9522
Missing (%)46.8%
Memory size159.0 KiB
0.0
5470 
1.0
5344 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters32442
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row1.0
3rd row0.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
0.05470
26.9%
1.05344
26.3%
(Missing)9522
46.8%

Length

2021-11-29T11:28:07.235952image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:28:07.285677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.05470
50.6%
1.05344
49.4%

Most occurring characters

ValueCountFrequency (%)
016284
50.2%
.10814
33.3%
15344
 
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number21628
66.7%
Other Punctuation10814
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
016284
75.3%
15344
 
24.7%
Other Punctuation
ValueCountFrequency (%)
.10814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common32442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
016284
50.2%
.10814
33.3%
15344
 
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII32442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
016284
50.2%
.10814
33.3%
15344
 
16.5%

Unit1-max
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing9522
Missing (%)46.8%
Memory size159.0 KiB
0.0
5470 
1.0
5344 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters32442
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row1.0
3rd row0.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
0.05470
26.9%
1.05344
26.3%
(Missing)9522
46.8%

Length

2021-11-29T11:28:07.338479image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:28:07.388283image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.05470
50.6%
1.05344
49.4%

Most occurring characters

ValueCountFrequency (%)
016284
50.2%
.10814
33.3%
15344
 
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number21628
66.7%
Other Punctuation10814
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
016284
75.3%
15344
 
24.7%
Other Punctuation
ValueCountFrequency (%)
.10814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common32442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
016284
50.2%
.10814
33.3%
15344
 
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII32442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
016284
50.2%
.10814
33.3%
15344
 
16.5%

Unit2-min
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing9522
Missing (%)46.8%
Memory size159.0 KiB
1.0
5470 
0.0
5344 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters32442
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row0.0
3rd row1.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
1.05470
26.9%
0.05344
26.3%
(Missing)9522
46.8%

Length

2021-11-29T11:28:07.441200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:28:07.491092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.05470
50.6%
0.05344
49.4%

Most occurring characters

ValueCountFrequency (%)
016158
49.8%
.10814
33.3%
15470
 
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number21628
66.7%
Other Punctuation10814
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
016158
74.7%
15470
 
25.3%
Other Punctuation
ValueCountFrequency (%)
.10814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common32442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
016158
49.8%
.10814
33.3%
15470
 
16.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII32442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
016158
49.8%
.10814
33.3%
15470
 
16.9%

Unit2-max
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing9522
Missing (%)46.8%
Memory size159.0 KiB
1.0
5470 
0.0
5344 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters32442
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row0.0
3rd row1.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
1.05470
26.9%
0.05344
26.3%
(Missing)9522
46.8%

Length

2021-11-29T11:28:07.545093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:28:07.594934image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.05470
50.6%
0.05344
49.4%

Most occurring characters

ValueCountFrequency (%)
016158
49.8%
.10814
33.3%
15470
 
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number21628
66.7%
Other Punctuation10814
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
016158
74.7%
15470
 
25.3%
Other Punctuation
ValueCountFrequency (%)
.10814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common32442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
016158
49.8%
.10814
33.3%
15470
 
16.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII32442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
016158
49.8%
.10814
33.3%
15470
 
16.9%

HospAdmTime-min
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct7152
Distinct (%)35.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-48.67841062
Minimum-3710.66
Maximum23.99
Zeros168
Zeros (%)0.8%
Negative19912
Negative (%)97.9%
Memory size159.0 KiB
2021-11-29T11:28:07.658777image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-3710.66
5-th percentile-236.12
Q1-34.135
median-2.77
Q3-0.02
95-th percentile-0.01
Maximum23.99
Range3734.65
Interquartile range (IQR)34.115

Descriptive statistics

Standard deviation143.6833182
Coefficient of variation (CV)-2.951684666
Kurtosis123.0885825
Mean-48.67841062
Median Absolute Deviation (MAD)2.75
Skewness-8.542504055
Sum-989875.48
Variance20644.89593
MonotonicityNot monotonic
2021-11-29T11:28:07.761143image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.023749
 
18.4%
-0.032290
 
11.3%
-0.011114
 
5.5%
-0.04658
 
3.2%
-0.05314
 
1.5%
0168
 
0.8%
-0.06136
 
0.7%
-0.0782
 
0.4%
-0.0840
 
0.2%
-0.0932
 
0.2%
Other values (7142)11752
57.8%
ValueCountFrequency (%)
-3710.661
< 0.1%
-3322.91
< 0.1%
-3269.11
< 0.1%
-3212.561
< 0.1%
-3141.551
< 0.1%
-2668.771
< 0.1%
-2562.531
< 0.1%
-2506.691
< 0.1%
-2476.581
< 0.1%
-2379.761
< 0.1%
ValueCountFrequency (%)
23.991
< 0.1%
22.041
< 0.1%
20.041
< 0.1%
17.341
< 0.1%
16.021
< 0.1%
14.651
< 0.1%
14.211
< 0.1%
141
< 0.1%
11.941
< 0.1%
10.991
< 0.1%

HospAdmTime-max
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct7152
Distinct (%)35.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-48.67841062
Minimum-3710.66
Maximum23.99
Zeros168
Zeros (%)0.8%
Negative19912
Negative (%)97.9%
Memory size159.0 KiB
2021-11-29T11:28:07.871186image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-3710.66
5-th percentile-236.12
Q1-34.135
median-2.77
Q3-0.02
95-th percentile-0.01
Maximum23.99
Range3734.65
Interquartile range (IQR)34.115

Descriptive statistics

Standard deviation143.6833182
Coefficient of variation (CV)-2.951684666
Kurtosis123.0885825
Mean-48.67841062
Median Absolute Deviation (MAD)2.75
Skewness-8.542504055
Sum-989875.48
Variance20644.89593
MonotonicityNot monotonic
2021-11-29T11:28:07.972454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.023749
 
18.4%
-0.032290
 
11.3%
-0.011114
 
5.5%
-0.04658
 
3.2%
-0.05314
 
1.5%
0168
 
0.8%
-0.06136
 
0.7%
-0.0782
 
0.4%
-0.0840
 
0.2%
-0.0932
 
0.2%
Other values (7142)11752
57.8%
ValueCountFrequency (%)
-3710.661
< 0.1%
-3322.91
< 0.1%
-3269.11
< 0.1%
-3212.561
< 0.1%
-3141.551
< 0.1%
-2668.771
< 0.1%
-2562.531
< 0.1%
-2506.691
< 0.1%
-2476.581
< 0.1%
-2379.761
< 0.1%
ValueCountFrequency (%)
23.991
< 0.1%
22.041
< 0.1%
20.041
< 0.1%
17.341
< 0.1%
16.021
< 0.1%
14.651
< 0.1%
14.211
< 0.1%
141
< 0.1%
11.941
< 0.1%
10.991
< 0.1%

ICULOS-min
Real number (ℝ≥0)

SKEWED

Distinct31
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.916256884
Minimum1
Maximum304
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:08.073386image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum304
Range303
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.852074093
Coefficient of variation (CV)2.010207569
Kurtosis4370.912417
Mean1.916256884
Median Absolute Deviation (MAD)0
Skewness59.42175818
Sum38969
Variance14.83847482
MonotonicityNot monotonic
2021-11-29T11:28:08.158150image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
112839
63.1%
23388
 
16.7%
31678
 
8.3%
41003
 
4.9%
5576
 
2.8%
6369
 
1.8%
7208
 
1.0%
8109
 
0.5%
960
 
0.3%
1029
 
0.1%
Other values (21)77
 
0.4%
ValueCountFrequency (%)
112839
63.1%
23388
 
16.7%
31678
 
8.3%
41003
 
4.9%
5576
 
2.8%
6369
 
1.8%
7208
 
1.0%
8109
 
0.5%
960
 
0.3%
1029
 
0.1%
ValueCountFrequency (%)
3041
 
< 0.1%
2821
 
< 0.1%
2691
 
< 0.1%
304
< 0.1%
281
 
< 0.1%
272
< 0.1%
262
< 0.1%
251
 
< 0.1%
241
 
< 0.1%
234
< 0.1%

ICULOS-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct231
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.77419355
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:08.257663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile16
Q126
median40
Q348
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.5524824
Coefficient of variation (CV)0.5670129396
Kurtosis42.39177693
Mean39.77419355
Median Absolute Deviation (MAD)11
Skewness4.846038135
Sum808848
Variance508.6144626
MonotonicityNot monotonic
2021-11-29T11:28:08.449717image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36693
 
3.4%
41655
 
3.2%
38651
 
3.2%
39637
 
3.1%
42629
 
3.1%
43628
 
3.1%
40621
 
3.1%
37614
 
3.0%
46604
 
3.0%
44583
 
2.9%
Other values (221)14021
68.9%
ValueCountFrequency (%)
888
 
0.4%
9101
 
0.5%
1086
 
0.4%
1196
 
0.5%
1296
 
0.5%
13123
0.6%
14155
0.8%
15187
0.9%
16222
1.1%
17282
1.4%
ValueCountFrequency (%)
3369
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3061
 
< 0.1%
3051
 
< 0.1%
3031
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2831
 
< 0.1%
2791
 
< 0.1%

SepsisLabel-min
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size159.0 KiB
0
20133 
1
 
203

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20336
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
020133
99.0%
1203
 
1.0%

Length

2021-11-29T11:28:08.549314image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:28:08.603109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
020133
99.0%
1203
 
1.0%

Most occurring characters

ValueCountFrequency (%)
020133
99.0%
1203
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
020133
99.0%
1203
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common20336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
020133
99.0%
1203
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII20336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
020133
99.0%
1203
 
1.0%

SepsisLabel-max
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size159.0 KiB
0
18546 
1
 
1790

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20336
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Length

2021-11-29T11:28:08.658606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:28:08.712474image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring characters

ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Common20336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII20336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Sepsis-min
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size159.0 KiB
0
18546 
1
 
1790

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20336
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Length

2021-11-29T11:28:08.768422image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:28:08.822335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring characters

ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Common20336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII20336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Sepsis-max
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size159.0 KiB
0
18546 
1
 
1790

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20336
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Length

2021-11-29T11:28:08.878176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:28:08.931892image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring characters

ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Common20336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII20336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
018546
91.2%
11790
 
8.8%

Hours-min
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct228
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.85793666
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:08.995236image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile15
Q125
median39
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.30865867
Coefficient of variation (CV)0.5741081639
Kurtosis40.49091179
Mean38.85793666
Median Absolute Deviation (MAD)11
Skewness4.703211094
Sum790215
Variance497.6762517
MonotonicityNot monotonic
2021-11-29T11:28:09.096118image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36700
 
3.4%
39665
 
3.3%
38656
 
3.2%
40634
 
3.1%
41632
 
3.1%
37632
 
3.1%
43600
 
3.0%
42597
 
2.9%
44580
 
2.9%
46560
 
2.8%
Other values (218)14080
69.2%
ValueCountFrequency (%)
8124
 
0.6%
9122
 
0.6%
1095
 
0.5%
11114
 
0.6%
12121
 
0.6%
13145
0.7%
14194
1.0%
15231
1.1%
16274
1.3%
17348
1.7%
ValueCountFrequency (%)
3365
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3052
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2791
 
< 0.1%
2771
 
< 0.1%

Hours-max
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct228
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.85793666
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:28:09.203146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile15
Q125
median39
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.30865867
Coefficient of variation (CV)0.5741081639
Kurtosis40.49091179
Mean38.85793666
Median Absolute Deviation (MAD)11
Skewness4.703211094
Sum790215
Variance497.6762517
MonotonicityNot monotonic
2021-11-29T11:28:09.303455image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36700
 
3.4%
39665
 
3.3%
38656
 
3.2%
40634
 
3.1%
41632
 
3.1%
37632
 
3.1%
43600
 
3.0%
42597
 
2.9%
44580
 
2.9%
46560
 
2.8%
Other values (218)14080
69.2%
ValueCountFrequency (%)
8124
 
0.6%
9122
 
0.6%
1095
 
0.5%
11114
 
0.6%
12121
 
0.6%
13145
0.7%
14194
1.0%
15231
1.1%
16274
1.3%
17348
1.7%
ValueCountFrequency (%)
3365
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3052
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2791
 
< 0.1%
2771
 
< 0.1%

Interactions

Correlations

2021-11-29T11:28:09.517606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-11-29T11:28:11.371003image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-11-29T11:28:13.137912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-11-29T11:28:14.795173image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-11-29T11:27:46.613652image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-11-29T11:27:48.995943image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-11-29T11:27:51.310003image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

PatientIDHR-minHR-maxO2Sat-minO2Sat-maxTemp-minTemp-maxSBP-minSBP-maxMAP-minMAP-maxDBP-minDBP-maxResp-minResp-maxEtCO2-minEtCO2-maxBaseExcess-minBaseExcess-maxHCO3-minHCO3-maxFiO2-minFiO2-maxpH-minpH-maxPaCO2-minPaCO2-maxSaO2-minSaO2-maxAST-minAST-maxBUN-minBUN-maxAlkalinephos-minAlkalinephos-maxCalcium-minCalcium-maxChloride-minChloride-maxCreatinine-minCreatinine-maxBilirubin_direct-minBilirubin_direct-maxGlucose-minGlucose-maxLactate-minLactate-maxMagnesium-minMagnesium-maxPhosphate-minPhosphate-maxPotassium-minPotassium-maxBilirubin_total-minBilirubin_total-maxTroponinI-minTroponinI-maxHct-minHct-maxHgb-minHgb-maxPTT-minPTT-maxWBC-minWBC-maxFibrinogen-minFibrinogen-maxPlatelets-minPlatelets-maxAge-minAge-maxGender-minGender-maxUnit1-minUnit1-maxUnit2-minUnit2-maxHospAdmTime-minHospAdmTime-maxICULOS-minICULOS-maxSepsisLabel-minSepsisLabel-maxSepsis-minSepsis-maxHours-minHours-max
0176.0117.085.0100.036.1137.4478.0181.044.00141.33NaNNaN17.032.0NaNNaN18.024.045.048.00.250.37.317.4086.0100.078.091.016.016.014.022.098.098.09.39.685.085.00.70.7NaNNaN133.0193.0NaNNaN2.02.23.33.73.84.60.30.3NaNNaN36.237.212.212.5NaNNaN5.714.7NaNNaN317.0338.083.1483.1400NaNNaNNaNNaN-0.03-0.0315400005454
1254.094.094.0100.036.0036.44114.0194.050.50116.0036.066.09.027.0NaNNaNNaNNaN22.022.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN100.0100.0NaNNaN7.97.9113.0113.02.52.5NaNNaN78.078.0NaNNaN2.52.54.44.45.15.1NaNNaNNaNNaN27.827.89.79.7NaNNaN11.011.0NaNNaN158.0158.075.9175.91000.00.01.01.0-98.60-98.6012300002323
2368.093.091.099.036.8938.61122.0159.062.6799.0044.069.017.040.0NaNNaN5.08.029.032.00.500.87.497.5138.041.0NaNNaNNaNNaN25.031.0NaNNaN10.911.198.0100.00.80.9NaNNaN51.0130.0NaNNaN2.42.52.32.93.44.1NaNNaNNaNNaN26.232.18.811.029.530.58.310.0NaNNaN465.0488.045.8245.82001.01.00.00.0-1195.71-1195.7114800004848
3493.0113.095.5100.036.0636.7890.0132.534.0084.0044.061.514.026.0NaNNaN0.00.022.022.0NaNNaN7.367.4141.045.097.598.0NaNNaN14.019.0NaNNaN8.28.2105.0108.00.80.8NaNNaN69.0253.0NaNNaN1.72.43.83.84.05.0NaNNaNNaNNaN24.027.68.38.321.322.37.67.6NaNNaN144.0220.065.7165.71000.00.01.01.0-8.77-8.7712900002929
4561.088.096.099.036.2237.33114.0150.073.00103.00NaNNaN14.021.0NaNNaNNaNNaN24.028.0NaNNaNNaNNaNNaNNaNNaNNaN16.030.06.09.062.080.07.88.5105.0106.00.60.7NaNNaN103.0138.0NaNNaN1.92.52.83.03.14.00.50.6NaNNaN39.745.714.215.529.029.04.78.1NaNNaN273.0288.028.0928.09111.01.00.00.0-0.05-0.0524900004848
5687.0111.095.0100.036.3336.72101.0150.073.00100.00NaNNaN18.543.0NaNNaN0.00.029.029.00.400.47.347.3447.047.0NaNNaNNaNNaN9.09.0NaNNaNNaNNaN111.0111.00.70.7NaNNaN68.0293.01.41.4NaNNaNNaNNaN3.83.8NaNNaNNaNNaN36.936.912.212.2NaNNaN12.012.0NaNNaN298.0298.052.0152.01111.01.00.00.0-0.03-0.0331900001717
67103.0155.593.0100.037.2838.3991.0147.559.00102.0045.082.012.033.0NaNNaN-12.0-6.013.020.00.401.07.227.4023.036.0NaNNaN452.0452.052.071.088.088.05.98.0111.0123.03.53.9NaNNaN71.0263.02.22.21.61.90.93.82.84.61.41.4NaNNaN36.746.014.516.425.427.17.29.7NaNNaN26.066.064.2464.24111.01.00.00.0-0.05-0.0514500004545
7865.088.079.0100.035.6736.8989.0136.057.0081.0040.056.012.022.0NaNNaN-11.0-6.015.017.0NaNNaN7.277.3722.037.0NaNNaNNaNNaN27.031.0NaNNaN7.48.2105.0110.01.11.3NaNNaN84.0129.00.82.11.82.52.73.83.25.7NaNNaNNaNNaN25.032.98.611.4NaNNaN9.011.4NaNNaN205.0357.087.0887.0811NaNNaNNaNNaN-2.23-2.2314000004040
8985.0143.089.5100.035.3339.3378.0158.056.00117.0044.0120.013.055.5NaNNaN-7.09.023.035.00.351.07.137.5132.080.574.099.0NaNNaN11.025.0NaNNaN7.48.7103.0113.00.71.3NaNNaN87.0143.00.83.81.12.41.75.43.04.5NaNNaNNaNNaN21.839.57.314.624.246.43.914.9124.0804.064.0759.027.9227.9211NaNNaNNaNNaN-0.03-0.0312580111258258
91063.084.090.0100.035.5037.7097.0137.063.0085.0047.065.010.023.0NaNNaN-3.00.023.025.00.401.07.327.4237.043.096.099.0NaNNaN17.018.0NaNNaNNaNNaN105.0109.00.91.1NaNNaN92.0116.01.11.12.12.1NaNNaN3.73.9NaNNaNNaNNaN27.932.89.510.929.929.98.79.9NaNNaN107.0115.076.7176.71000.00.01.01.0-2.36-2.3632500002323

Last rows

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